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Nadio Granata, SF Society Magazine | Conga Connect West at Dreamforce 2018


 

(upbeat music) >> From San Francisco it's theCUBE. Covering Conga Connect West 2018. Brought to you by Conga. >> Hey welcome back, everybody, Jeff Frick here with theCUBE We are winding things down, or winding things up I'm not quite sure here at the Conga Connect West event 3,000, all dancing with their headphones on silent disco. We're excited to have the launch of a brand new magazine SF Society magazine. The managing director, Nadio Granata. Nadio, congratulations you just launched this today. >> We did yes, thank you, Jeff, yeah. >> So what is the objective, what is this all about? SF Society >> SF Society. It's about raising the profile of the partners in the SalesForce, I can see these guys, >> Like these guys, their profile is raised, so, so what was missing, what motivated, it's a lot of work to do a magazine. >> Okay, it is, it is. It's been a labor of love, I got to tell you that, but, SalesForce is a fantastic job, for SalesForce for its employees, within SalesForce but the partners, we want to raise an independent voice of the partners. And we talk about success, we talk about philanthropy, we talk about all the great things that going on, and most importantly the community. So that's what the magazine is about. >> There's just one problem though, Nadio. How many of these did you print? (laughing) >> Well, you know, I've got to be cautious, I had to be cautious, but we've printed, we've printed 5,000 for today, it's online and we expect to generate about 100,000 readership very, very quickly. >> Okay good, but I got good news and bad news. >> Go on. >> Did you hear the keynote? >> Yes I did. Yeah, yeah, yeah, yeah. >> How many people are here? >> Oh I know there's a lot of people here. >> 171,000. So you, 5 plus 100, you got to go back to the printer. >> We're cautious, we're cautious. >> Alright, alright good. >> Thank you. >> So who's supporting this? Are you getting advertising to support it, how's it being supported? >> Yes, it's sponsored by advertisers, so Conga of course a great advertiser in there, we've got NataBox in there, we've got New Voice Media, we've got FRG, we've got loads of companies >> Have you got more magazines? >> Very positive, very positive >> Get those out of here. >> So, sponsored by advertising and that's the way forward. >> And how often does it come out? >> Quarterly. It's a quarterly magazine. >> A quarterly magazine. >> Ya it's global, we've got content from all over the world and we're looking to grow, it's a 48 page production, we're looking to grow that as we go forward. >> Kay, what's the online address, for people who need more information. >> Okay www.sfsocietymagazine.com >> Sfsocietymagazine.com check it out >> Yeah, that's not easy to say >> Quick, there's only 4,999 of em left and you're competing with 170,000 people. Alright. >> But get it online, guys, get it online. >> Get it online. Alright, Nadio thanks for taking a few minutes and nothing but best of luck on this thing. >> Thanks, Jeff. >> Alright, he's Nadio, I'm Jeff, you're watching theCUBE we're at Conga, Connect West and SalesForce downtown San Francisco, come on down the party's just beginning. (upbeat music)

Published Date : Sep 26 2018

SUMMARY :

Brought to you by Conga. We're excited to have the It's about raising the profile of to do a magazine. I got to tell you that, How many of these did you print? I had to be cautious, but we've printed, Okay good, but I got Yeah, yeah, yeah, yeah. to go back to the printer. and that's the way forward. It's a quarterly magazine. Ya it's global, we've got for people who need more information. 4,999 of em left and you're best of luck on this thing. the party's just beginning.

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Eric Herzog, Infinidat | CUBEConversation


 

>>Hey everyone, welcome to this cube conversation. I'm your host Lisa Martin, and I have the pleasure of welcoming back our most prolific guest on the cube in its history, the CMO of Fin Ad, Eric Herzog. Eric, it's great to see you. Welcome back, >>Lisa. It's great to be here. Love being on the cube. I think this might be number 55 or 56. Been doing 'em a long time with the Cube. You guys are great. >>You, you have, and we always recognize you lately with the Hawaiian shirts. It's your brand that's, that's the Eric Hizo brand. We love it. But I like the pin, the infin nut pin on brand. Thank you. >>Yeah. Oh, gotta be on brand. >>Exactly. So talk about the current IT landscape. So much change we've seen in the last couple of years. Specifically, what are some of the big challenges that you are talking with enterprise customers and cloud service providers? About what, what are some of those major things on their minds? >>So there's a couple things. First of all is obviously with the Rocky economy and even before covid, just for storage in particular, CIOs hate storage. I've been doing this now since 1986. I have never, ever, ever met a CIO at any company I've bid with. And I've been with four of the biggest storage companies on this planet. Never met a cio. Used to be a storage guy. So they know they need it, but boy, they really don't like it. So the storage admins have to manage more and more storage. Exabytes, exabytes, it just ballooning for what a storage admin has to do. Then you then have the covid and is it recession? No. Is it a growth? And then clearly what's happened in the last year with what's going on in Europe and the, is it a recession, the inflation. So they're always looking to, how do we cut money on storage yet still get what we need for our applications, workloads, and use cases. So that's definitely the biggest, the first topic. >>So never met a CIO that was a storage admin or as a fan, but as you point out, they need it. And we've seen needs changing in customer landscapes, especially as the threat landscape has changed so dramatically the last couple of years. Ransomware, you've said it before, I say it too. It's no longer if it's when it's how often. It's the frequency. We've gotta be able to recover. Backups are being targeted. Talk to me about some of, in that landscape, some of the evolutions of customer challenges and maybe those CIOs going, We've gotta make sure that our, our storage data is protected. >>So it's starting to change. However, historically with the cio and then when they started hiring CISOs or security directors, whatever they had, depending on the company size, it was very much about protecting the edge. Okay, if you will, the moat and the wall of the castle. Then it was the network in between. So keep the streets inside the castle clean. Then it was tracking down the bad guy. So if they did get over, the issue is, if I remember correctly, the sheriff of Nottingham never really caught Robinhood. So the problem is the dwell time where the ransomware malware's hidden on storage could be as much as 200 days. So I think they're starting to realize at the security level now, forget, forget the guys on the storage side, the security guys, the cso, the CIO, are starting to realize that if you're gonna have a comprehensive cybersecurity strategy, must include storage. And that is new >>That, well, that's promising then. That's new. I mean obviously promising given the, the challenges and the circumstances. So then from a storage perspective, customers that are in this multi-cloud hybrid cloud environment, you talked about the the edge cloud on-prem. What are some of the key things from a storage perspective that customers have to achieve these days to be secure as data volumes continue to grow and spread? >>So what we've done is implement on both primary storage and secondary storage and technology called infin safe. So Infin Safe has the four legs of the storage cyber security stool. So first of all is creating an air gap. In this case, a logical air gap can be local or remote. We create an immutable snapshot, which means it can't be changed, it can't be altered, so you can't change it. We have a fenced forensic environment to check out the storage because you don't wanna recover. Again, malware and rans square can is hidden. So you could be making amenable snapshots of actually malware, ransomware, and never know you're doing it right. So you have to check it out. Then you need to do a rapid recovery. The most important thing if you have an attack is how fast can you be up and going with recovery? So we have actually instituted now a number of cyber storage security guarantees. >>We will guarantee the SLAs on a, the snapshot is absolutely immutable. So they know that what they're getting is what they were supposed to be getting. And then also we are guaranteeing recovery times on primary storage. We're guaranteeing recovery of under one minute. We'll make the snapshot available under one minute and on secondary storage under 20 minutes. So those are things you gotta look for from a security perspective. And then the other thing you gotta practice, in my world, ransomware, malware, cyber tech is basically a disaster. So yes, you got the hurricane, yes, you got the flood, yes, you got the earthquake. Yes, you got the fire in the building. Yes you got whatever it may be. But if you don't practice malware, ransomware, recoveries and protection, then it might as well be a hurricane or earthquake. It will take your data, >>It will take your data on the numbers of customers that pay ransom is pretty high, isn't it? And and not necessarily able to recover their data. So it's a huge risk. >>So if you think about it, the government documented that last year, roughly $6 trillion was spent either protecting against ransomware and malware or paying ransomware attacks. And there's been several famous ones. There was one in Korea, 72 million ransom. It was one of the Korea's largest companies. So, and those are only the ones that make the news. Most of 'em don't make the news. Right. >>So talk to me then, speaking and making the news. Nobody wants to do that. We, we know every industry is vulnerable to this. Some of the ones that might be more vulnerable, healthcare, government, public sector education. I think the Los Angeles Unified School district was just hit as well in September. They >>Were >>What, talk to me about how infin out is helping customers really dial down the risk when the threat actors are becoming more and more sophisticated? >>Well, there's a couple things. First of all, our infin safe software comes free on our main product. So we have a product called infin Guard for Secondary Storage and it comes for free on that. And then our primary storage product's called the Infin Box. It also comes for free. So they don't have to use it, but we embed it. And then we have reference architectures that we give them our ses, our solutions architects and our technical advisors all up to speed on why they should do it, how they should do it. We have a number of customers doing it. You know, we're heavily concentrated the global Fortune 2000, for example, we publicly announced that 26% of the Fortune 50 use our technology, even though we're a small company. So we go to extra lengths to a B, educated on our own front, our own teams, and then B, make sure they portray that to the end users and our channel partners. But the end users don't pay a dime for the software that does what I just described, it's free, it's included when you get you're Infin box or you're ingar, it's included at no charge. >>That's pretty differentiating from a competitive standpoint. I might, I would guess >>It is. And also the guarantee. So for example, on primary storage, okay, whether you'd put your Oracle or put your SAP or I Mongo or your sequel or your highly transactional workloads, right? Your business finance workload, all your business critical stuff. We are the first and only storage company that offers a primary guarantee on cyber storage resilience. And we offer two of them on primary storage. No other vendor offers a guarantee, which we do on primary storage. Whether you the first and right now as of here we are sitting in the middle of October. We are still the only vendor that offers anything on primary storage from a guaranteed SLA on primary storage for cyber storage resilience. >>Let's talk about those guarantees. Walk me through what you just announced. There's been a a very, a lot of productivity at Infin DAT in 2022. A lot of things that you've announced but on crack some of the things you're announcing. Sure. Talk to me specifically about those guarantees and what's in it for me as a customer. It sounds pretty obvious, but I'd love to hear it from you. >>Okay, so we've done really three different types of guarantees. The first one is we have a hundred percent availability guarantee on our primary storage. And we've actually had that for the last, since 2019. So it's a hundred percent availability. We're guaranteed no downtime, a hundred percent availability, which for our customer base being heavily concentrated, the global Fortune 2000 large government enterprises, big universities and even smaller companies, we do a lot of business with CSPs and MSPs. In fact, at the Flash Memory Summit are Infin Box ssa All Flash was named the best product for hyperscaler deployment. Hyperscaler basically means cloud servers provider. So they need a hundred percent availability. So we have a guarantee on that. Second guarantee we have is a performance guarantee. We'll do an analysis, we look at all their workloads and then we will guarantee in writing what the performance should be based on which, which of our products they want to buy are Infin Box or Infin Box ssa, which is all flash. >>Then we have the third one is all about cyber resilience. So we have two on our Infin box, our Infin box SSA for primary storage, which is a one the immutability of the snapshot and immediately means you can't erase the data. Right? Camp tamper with it. Second one is on the recovery time, which is under a minute. We just announced in the middle of October that we are doing a similar cyber storage resilience guarantee on our ARD secondary product, which is designed for backup recovery, et cetera. We will also offer the immutably snapshot guarantee and also one on the recoverability of that data in under 20 minutes. In fact, we just did a demo at our live launch earlier this week and we demoed 20 petabytes of Veeam backup data recovered in 12 minutes. 12 >>Minutes 2012. >>20 petabytes In >>12 bytes in 12 minutes. Yes. That's massive. That's massively differentiating. But that's essential for customers cuz you know, in terms of backups and protecting the data, it's all about recovery >>A and once they've had the attack, it's how fast you get back online, right? That that's what happens if they've, if they can't stop the attack, can't stop the threat and it happens. They need to get that back as fast as they can. So we have the speed of recovery on primary stores, the first in the industry and we have speed on the backup software and we'll do the same thing for a backup data set recovery as well. Talk >>To me about the, the what's in it for me, For the cloud service providers, they're obviously the ones that you work with are competing with the hyperscalers. How does the guarantees and the differentiators that Fin out is bringing to market? How do you help those cloud SPS dial up their competitiveness against the big cheeses? >>Well, what we do is we provide that underlying infrastructure. We, first of all, we only sell things that are petabyte in scale. That's like always sell. So for example, on our in fitter guard product, the raw capacity is over four petabytes. And the effective capacity, cuz you do data reduction is over 85 petabytes on our newest announced product, on our primary storage product, we now can do up to 17 petabytes of effective capacity in a single rack. So the value to the service rider is they can save on what slots? Power and floor. A greener data center. Yeah, right. Which by the way is not just about environmentals, but guess what? It also translate into operational expense. >>Exactly. CapEx office, >>With a lot of these very large systems that we offer, you can consolidate multiple products from our competitors. So for example, with one of the competitors, we had a deal that we did last quarter 18 competitive arrays into one of ours. So talk about saving, not just on all of the operational expense, including operational manpower, but actually dramatically on the CapEx. In fact, one of our Fortune 500 customers in the telco space over the last five years have told us on CapEx alone, we've saved them $104 million on CapEx by consolidating smaller technology into our larger systems. And one of the key things we do is everything is automated. So we call it autonomous automation use AI based technology. So once you install it, we've got several public references who said, I haven't touched this thing in three or four years. It automatically configures itself. It automatically adjusts to changes in performance and new apps. When I put in point a new app at it automatically. So in the old days the storage admin would optimize performance for a new application. We don't do that, we automatically do it and autonomously the admin doesn't even click a button. We just sense there's new applications and we automate ourselves and configure ourselves without the admin having to do anything. So that's about saving operational expense as well as operational manpower. >>Absolutely. I was, one of the things that was ringing in my ear was workforce productivity and obviously those storage admins being able to to focus on more strategic projects. Can't believe the CIOs aren't coming around yet. But you said there's, there's a change, there's a wave coming. But if we think about the the, the what's in it for me as a customer, the positive business outcomes that I'm hearing, lower tco, your greener it, which is key. So many customers that we talk to are so focused on sustainability and becoming greener, especially with an on-prem footprint, workforce productivity. Talk about some of the other key business outcomes that you're helping customers achieve and how it helps them to be more competitive. >>Sure. So we've got a, a couple different things. First of all, storage can't go down. When the storage goes down, everyone gets blamed. Mission. When an app goes down, no one really thinks about it. It's always the storage guy's fault. So you want to be a hundred percent available. And that's today's businesses, and I'd actually argue it's been this way for 20 years are 24 by seven by 365. So that's one thing that we deliver. Second thing is performance. So we have public references talk about their SAP workload that used to take two hours, now takes 20 minutes, okay? We have another customer that was doing SAP queries. They improved their performance three times, Not 3%, not 3%, three times. So 300% better performance just by using our storages. They didn't touch the sap, they didn't touch the servers. All they do is to put our storage in there. >>So performance relates basically to applications, workloads and use cases and productivity beyond it. So think the productivity of supply chain guys, logistics guys, the shipping guys, the finance guys, right? All these applications that run today's enterprises. So we can automate all that. And then clearly the cyber threat. Yeah, that is a huge issue. And every CIO is concerned about the cyber threat. And in fact, it was interesting, Fortune magazine did a survey of CEOs, and this was last May, the number one concern, 66% in that may survey was cyber security number one concern. So this is not just a CIO thing, this is a CEO thing and a board level >>Thing. I was gonna say it's at at the board level that the cyber security threats are so real, they're so common. No one wants to be the next headline, like the colonial pipeline, right? Or the school districts or whatnot. And everybody is at risk. So then what you're enabling with what you've just announced, the all the guarantees on the SLAs, the massively fast recovery times, which is critical in cyber recovery. Obviously resilience is is key there. Modern data protection it sounds like to me. How do you define that and and what are customers looking for with respect to modern cyber resilience versus data protection? >>Yeah, so we've got normal data protection because we work with all the backup vendors. Our in ARD is what's known as a purpose built backup appliance. So that allows you to back at a much faster rate. And we work all the big back backup vendors, IBM spectrum Protect, we work with veritas vem com vault, oracle arm, anybody who does backup. So that's more about the regular side, the traditional backup. But the other part of modern data protection is infusing that with the cyber resilience. Cuz cyber resilience is a new thing. Yes, from a storage guy perspective, it hasn't been around a long time. Many of our competitors have almost nothing. One or two of our competitors have a pretty robust, but they don't guarantee it the way we guarantee it. So they're pretty good at it. But the fact that we're willing to put our money where our mouth is, we think says we price stand above and then most of the other guys in the storage industry are just starting to get on the bandwagon of having cyber resilience. >>So that changes what you do from data protection, what would call modern data protection is a combination of traditional backup recovery, et cetera. Now with this influence and this infusion of cybersecurity cyber resilience into a storage environment. And then of course we've also happened to add it on primary storage as well. So whether it's primary storage or backup and archive storage, we make sure you have that right cyber resilience to make it, if you will, modern data protection and diff different from what it, you know, the old backup of your grandfather, father, son backup in tape or however you used to do it. We're well beyond that now we adding this cyber resilience aspect. Well, >>From a cyber resilience perspective, ransomware, malware, cyber attacks are, that's a disaster, right? But traditional disaster recovery tools aren't really built to be able to pull back that data as quickly as it sounds like in Trinidad is able to facilitate. >>Yeah. So one of the things we do is in our reference architectures and written documentation as well as when we do the training, we'd sell the customers you need to practice, if you practice when there's a fire, a flood, a hurricane, an earthquake or whatever is the natural disaster you're practicing that you need to practice malware and ran somewhere. And because our recovery is so rapid and the case of our ingar, our fenced environment to do the testing is actually embedded in it. Several of our competitors, if you want the fenced environment, you have to buy a second product with us. It's all embedded in the one item. So A, that makes it more effective from a CapEx and opex perspective, but it also makes it easier. So we recommend that they do the practice recoveries monthly. Now whether they do it or not separate issue, but at least that's what we're recommending and say, you should be doing this on a monthly basis just like you would practice a disaster, like a hurricane or fire or a flood or an earthquake. Need to be practicing. And I think people are starting to hear it, but they don't still think more about, you know, the flood. Yeah. Or about >>The H, the hurricane. >>Yeah. That's what they think about. They not yet thinking about cybersecurity as really a disaster model. And it is. >>Absolutely. It is. Is is the theme of cyber resilience, as you said, this is a new concept, A lot of folks are talking about it, applying it differently. Is that gonna help dial up those folks just really being much more prepared for that type of cyber disaster? >>Well, we've made it so it's automated. Once you set up the immutable snapshots, it just does its thing. You don't set it and forget it. We create the logical air back. Once you do it, same thing. Set it and forget it. The fence forensic environment, easy to deploy. You do have to just configure it once and then obviously the recovery is almost instantaneous. It's under a minute guaranteed on primary storage and under 20 minutes, like I told you when we did our launch this week, we did 20 petabytes of Veeam backup data in 12 minutes. So that's pretty incredible. That's a lot of data to have recovered in 12 minutes. So the more automated we make it, which is what our real forte is, is this autonomous automation and automating as much as possible and make it easy to configure when you do have to configure. That's what differentiates what we do from our perspective. But overall in the storage industry, it's the recognition finally by the CISOs and the CIOs that, wait a second, maybe storage might be an essential part of my corporate cybersecurity strategy. Yes. Which it has not been historically, >>But you're seeing that change. Yes. >>We're starting to see that change. >>Excellent. So talk to me a little bit before we wrap here about the go to market one. Can folks get their hands on the updates to in kindergar and Finn and Safe and Penta box? >>So all these are available right now. They're available now either through our teams or through our, our channel partners globally. We do about 80% of our business globally through the channel. So whether you talk to us or talk to our channel partners, we're there to help. And again, we put our money where your mouth is with those guarantees, make sure we stand behind our products. >>That's awesome. Eric, thank you so much for joining me on the program. Congratulations on the launch. The the year of productivity just continues for infinit out is basically what I'm hearing. But you're really going in the extra mile for customers to help them ensure that the inevitable cyber attacks, that they, that they're complete storage environment on prem will be protected and more importantly, recoverable Very quickly. We appreciate your insights and your input. >>Great. Absolutely love being on the cube. Thank you very much for having us. Of >>Course. It's great to have you back. We appreciate it. For Eric Herzog, I'm Lisa Martin. You're watching this cube conversation live from Palo Alto.

Published Date : Oct 12 2022

SUMMARY :

and I have the pleasure of welcoming back our most prolific guest on the cube in Love being on the cube. But I like the pin, the infin nut pin on brand. So talk about the current IT landscape. So the storage admins have to manage more and more So never met a CIO that was a storage admin or as a fan, but as you point out, they need it. So the problem is the dwell time where the ransomware malware's hidden on storage could be as much as 200 days. So then from a storage perspective, customers that are in this multi-cloud hybrid cloud environment, So Infin Safe has the four legs of the storage cyber security stool. So yes, you got the hurricane, yes, you got the flood, yes, you got the earthquake. And and not necessarily able to recover their data. So if you think about it, the government documented that last year, So talk to me then, speaking and making the news. So we have a product called infin Guard for Secondary Storage and it comes for free I might, I would guess We are the first and only storage company that offers a primary guarantee on cyber on crack some of the things you're announcing. So we have a guarantee on that. in the middle of October that we are doing a similar cyber cuz you know, in terms of backups and protecting the data, it's all about recovery of recovery on primary stores, the first in the industry and we have speed on the backup software How does the guarantees and the differentiators that Fin And the effective capacity, cuz you do data reduction Exactly. So in the old days the storage admin would optimize performance for a new application. So many customers that we talk to are so focused on sustainability So that's one thing that we deliver. So performance relates basically to applications, workloads and use cases and productivity beyond it. So then what you're enabling with what you've just announced, So that's more about the regular side, the traditional backup. So that changes what you do from data protection, what would call modern data protection is a combination of traditional built to be able to pull back that data as quickly as it sounds like in Trinidad is able to facilitate. And because our recovery is so rapid and the case And it is. Is is the theme of cyber resilience, as you said, So the more automated we make it, which is what our real forte is, But you're seeing that change. So talk to me a little bit before we wrap here about the go to market one. So whether you talk to us or talk to our channel partners, we're there to help. Congratulations on the launch. Absolutely love being on the cube. It's great to have you back.

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The University of Edinburgh and Rolls Royce Drive in Exascale Style | Exascale Day


 

>>welcome. My name is Ben Bennett. I am the director of HPC Strategic programs here at Hewlett Packard Enterprise. It is my great pleasure and honor to be talking to Professor Mark Parsons from the Edinburgh Parallel Computing Center. And we're gonna talk a little about exa scale. What? It means we're gonna talk less about the technology on Maura about the science, the requirements on the need for exa scale. Uh, rather than a deep dive into the enabling technologies. Mark. Welcome. >>I then thanks very much for inviting me to tell me >>complete pleasure. Um, so I'd like to kick off with, I suppose. Quite an interesting look back. You and I are both of a certain age 25 plus, Onda. We've seen these milestones. Uh, I suppose that the S I milestones of high performance computing's come and go, you know, from a gig a flop back in 1987 teraflop in 97 a petaflop in 2000 and eight. But we seem to be taking longer in getting to an ex a flop. Um, so I'd like your thoughts. Why is why is an extra flop taking so long? >>So I think that's a very interesting question because I started my career in parallel computing in 1989. I'm gonna join in. IPCC was set up then. You know, we're 30 years old this year in 1990 on Do you know the fastest computer we have them is 800 mega flops just under a getting flogged. So in my career, we've gone already. When we reached the better scale, we'd already gone pretty much a million times faster on, you know, the step from a tariff block to a block scale system really didn't feel particularly difficult. Um, on yet the step from A from a petaflop PETA scale system. To an extent, block is a really, really big challenge. And I think it's really actually related to what's happened with computer processes over the last decade, where, individually, you know, approached the core, Like on your laptop. Whoever hasn't got much faster, we've just got more often So the perception of more speed, but actually just being delivered by more course. And as you go down that approach, you know what happens in the supercomputing world as well. We've gone, uh, in 2010 I think we had systems that were, you know, a few 1000 cores. Our main national service in the UK for the last eight years has had 118,000 cores. But looking at the X scale we're looking at, you know, four or five million cores on taming that level of parallelism is the real challenge. And that's why it's taking an enormous and time to, uh, deliver these systems. That is not just on the hardware front. You know, vendors like HP have to deliver world beating technology and it's hard, hard. But then there's also the challenge to the users. How do they get the codes to work in the face of that much parallelism? >>If you look at what the the complexity is delivering an annex a flop. Andi, you could have bought an extra flop three or four years ago. You couldn't have housed it. You couldn't have powered it. You couldn't have afforded it on, do you? Couldn't program it. But you still you could have You could have bought one. We should have been so lucky to be unable to supply it. Um, the software, um I think from our standpoint, is is looking like where we're doing mawr enabling with our customers. You sell them a machine on, then the the need then to do collaboration specifically seems mawr and Maura around the software. Um, so it's It's gonna be relatively easy to get one x a flop using limb pack, but but that's not extra scale. So what do you think? On exa scale machine versus an X? A flop machine means to the people like yourself to your users, the scientists and industry. What is an ex? A flop versus >>an exa scale? So I think, you know, supercomputing moves forward by setting itself challenges. And when you when you look at all of the excess scale programs worldwide that are trying to deliver systems that can do an X a lot form or it's actually very arbitrary challenge. You know, we set ourselves a PETA scale challenge delivering a petaflop somebody manage that, Andi. But you know, the world moves forward by setting itself challenges e think you know, we use quite arbitrary definition of what we mean is well by an exit block. So, you know, in your in my world, um, we either way, first of all, see ah flop is a computation, so multiply or it's an ad or whatever on we tend. Thio, look at that is using very high precision numbers or 64 bit numbers on Do you know, we then say, Well, you've got to do the next block. You've got to do a billion billion of those calculations every second. No, a some of the last arbitrary target Now you know today from HPD Aiken by my assistant and will do a billion billion calculations per second. And they will either do that as a theoretical peak, which would be almost unattainable, or using benchmarks that stressed the system on demonstrate a relaxing law. But again, those benchmarks themselves attuned Thio. Just do those calculations and deliver and explore been a steady I'll way if you like. So, you know, way kind of set ourselves this this this big challenge You know, the big fence on the race course, which were clambering over. But the challenge in itself actually should be. I'm much more interesting. The water we're going to use these devices for having built um, eso. Getting into the extra scale era is not so much about doing an extra block. It's a new generation off capability that allows us to do better scientific and industrial research. And that's the interesting bit in this whole story. >>I would tend to agree with you. I think the the focus around exa scale is to look at, you know, new technologies, new ways of doing things, new ways of looking at data and to get new results. So eventually you will get yourself a nexus scale machine. Um, one hopes, sooner rather >>than later. Well, I'm sure you don't tell me one, Ben. >>It's got nothing to do with may. I can't sell you anything, Mark. But there are people outside the door over there who would love to sell you one. Yes. However, if we if you look at your you know your your exa scale machine, Um, how do you believe the workloads are going to be different on an extra scale machine versus your current PETA scale machine? >>So I think there's always a slight conceit when you buy a new national supercomputer. On that conceit is that you're buying a capability that you know on. But many people will run on the whole system. Known truth. We do have people that run on the whole of our archer system. Today's A 118,000 cores, but I would say, and I'm looking at the system. People that run over say, half of that can be counted on Europe on a single hand in a year, and they're doing very specific things. It's very costly simulation they're running on. So, you know, if you look at these systems today, two things show no one is. It's very difficult to get time on them. The Baroque application procedures All of the requirements have to be assessed by your peers and your given quite limited amount of time that you have to eke out to do science. Andi people tend to run their applications in the sweet spot where their application delivers the best performance on You know, we try to push our users over time. Thio use reasonably sized jobs. I think our average job says about 20,000 course, she's not bad, but that does mean that as we move to the exits, kill two things have to happen. One is actually I think we've got to be more relaxed about giving people access to the system, So let's give more people access, let people play, let people try out ideas they've never tried out before. And I think that will lead to a lot more innovation and computational science. But at the same time, I think we also need to be less precious. You know, we to accept these systems will have a variety of sizes of job on them. You know, we're still gonna have people that want to run four million cores or two million cores. That's absolutely fine. Absolutely. Salute those people for trying really, really difficult. But then we're gonna have a huge spectrum of views all the way down to people that want to run on 500 cores or whatever. So I think we need Thio broaden the user base in Alexa Skill system. And I know this is what's happening, for example, in Japan with the new Japanese system. >>So, Mark, if you cast your mind back to almost exactly a year ago after the HPC user forum, you were interviewed for Premier Magazine on Do you alluded in that article to the needs off scientific industrial users requiring, you know, uh on X a flop or an exa scale machine it's clear in your in your previous answer regarding, you know, the workloads. Some would say that the majority of people would be happier with, say, 10 100 petaflop machines. You know, democratization. More people access. But can you provide us examples at the type of science? The needs of industrial users that actually do require those resources to be put >>together as an exa scale machine? So I think you know, it's a very interesting area. At the end of the day, these systems air bought because they are capability systems on. I absolutely take the argument. Why shouldn't we buy 10 100 pattern block systems? But there are a number of scientific areas even today that would benefit from a nexus school system and on these the sort of scientific areas that will use as much access onto a system as much time and as much scale of the system as they can, as you can give them eso on immediate example. People doing chroma dynamics calculations in particle physics, theoretical calculations, they would just use whatever you give them. But you know, I think one of the areas that is very interesting is actually the engineering space where, you know, many people worry the engineering applications over the last decade haven't really kept up with this sort of supercomputers that we have. I'm leading a project called Asimov, funded by M. P S O. C in the UK, which is jointly with Rolls Royce, jointly funded by Rolls Royce and also working with the University of Cambridge, Oxford, Bristol, Warrick. We're trying to do the whole engine gas turbine simulation for the first time. So that's looking at the structure of the gas turbine, the airplane engine, the structure of it, how it's all built it together, looking at the fluid dynamics off the air and the hot gasses, the flu threat, looking at the combustion of the engine looking how fuel is spread into the combustion chamber. Looking at the electrics around, looking at the way the engine two forms is, it heats up and cools down all of that. Now Rolls Royce wants to do that for 20 years. Andi, Uh, whenever they certify, a new engine has to go through a number of physical tests, and every time they do on those tests, it could cost them as much as 25 to $30 million. These are very expensive tests, particularly when they do what's called a blade off test, which would be, you know, blade failure. They could prove that the engine contains the fragments of the blade. Sort of think, continue face really important test and all engines and pass it. What we want to do is do is use an exa scale computer to properly model a blade off test for the first time, so that in future, some simulations can become virtual rather than having thio expend all of the money that Rolls Royce would normally spend on. You know, it's a fascinating project is a really hard project to do. One of the things that I do is I am deaf to share this year. Gordon Bell Price on bond I've really enjoyed to do. That's one of the major prizes in our area, you know, gets announced supercomputing every year. So I have the pleasure of reading all the submissions each year. I what's been really interesting thing? This is my third year doing being on the committee on what's really interesting is the way that big systems like Summit, for example, in the US have pushed the user communities to try and do simulations Nowhere. Nobody's done before, you know. And we've seen this as well, with papers coming after the first use of the for Goku system in Japan, for example, people you know, these are very, very broad. So, you know, earthquake simulation, a large Eddie simulations of boats. You know, a number of things around Genome Wide Association studies, for example. So the use of these computers spans of last area off computational science. I think the really really important thing about these systems is their challenging people that do calculations they've never done before. That's what's important. >>Okay, Thank you. You talked about challenges when I nearly said when you and I had lots of hair, but that's probably much more true of May. Um, we used to talk about grand challenges we talked about, especially around the teraflop era, the ski red program driving, you know, the grand challenges of science, possibly to hide the fact that it was a bomb designing computer eso they talked about the grand challenges. Um, we don't seem to talk about that much. We talk about excess girl. We talk about data. Um Where are the grand challenges that you see that an exa scale computer can you know it can help us. Okay, >>so I think grand challenges didn't go away. Just the phrase went out of fashion. Um, that's like my hair. I think it's interesting. The I do feel the science moves forward by setting itself grand challenges and always had has done, you know, my original backgrounds in particle physics. I was very lucky to spend four years at CERN working in the early stage of the left accelerator when it first came online on. Do you know the scientists there? I think they worked on left 15 years before I came in and did my little ph d on it. Andi, I think that way of organizing science hasn't changed. We just talked less about grand challenges. I think you know what I've seen over the last few years is a renaissance in computational science, looking at things that have previously, you know, people have said have been impossible. So a couple of years ago, for example, one of the key Gordon Bell price papers was on Genome Wide Association studies on some of it. If I may be one of the winner of its, if I remember right on. But that was really, really interesting because first of all, you know, the sort of the Genome Wide Association Studies had gone out of favor in the bioinformatics by a scientist community because people thought they weren't possible to compute. But that particular paper should Yes, you could do these really, really big Continental little problems in a reasonable amount of time if you had a big enough computer. And one thing I felt all the way through my career actually is we've probably discarded Mawr simulations because they were impossible at the time that we've actually decided to do. And I sometimes think we to challenge ourselves by looking at the things we've discovered in the past and say, Oh, look, you know, we could actually do that now, Andi, I think part of the the challenge of bringing an extra service toe life is to get people to think about what they would use it for. That's a key thing. Otherwise, I always say, a computer that is unused to just be turned off. There's no point in having underutilized supercomputer. Everybody loses from that. >>So Let's let's bring ourselves slightly more up to date. We're in the middle of a global pandemic. Uh, on board one of the things in our industry has bean that I've been particularly proud about is I've seen the vendors, all the vendors, you know, offering up machine's onboard, uh, making resources available for people to fight things current disease. Um, how do you see supercomputers now and in the future? Speeding up things like vaccine discovery on help when helping doctors generally. >>So I think you're quite right that, you know, the supercomputer community around the world actually did a really good job of responding to over 19. Inasmuch as you know, speaking for the UK, we put in place a rapid access program. So anybody wanted to do covert research on the various national services we have done to the to two services Could get really quick access. Um, on that, that has worked really well in the UK You know, we didn't have an archer is an old system, Aziz. You know, we didn't have the world's largest supercomputer, but it is happily bean running lots off covert 19 simulations largely for the biomedical community. Looking at Druk modeling and molecular modeling. Largely that's just been going the US They've been doing really large uh, combinatorial parameter search problems on on Summit, for example, looking to see whether or not old drugs could be reused to solve a new problem on DSO, I think, I think actually, in some respects Kobe, 19 is being the sounds wrong. But it's actually been good for supercomputing. Inasmuch is pointed out to governments that supercomputers are important parts off any scientific, the active countries research infrastructure. >>So, um, I'll finish up and tap into your inner geek. Um, there's a lot of technologies that are being banded around to currently enable, you know, the first exa scale machine, wherever that's going to be from whomever, what are the current technologies or emerging technologies that you are interested in excited about looking forward to getting your hands on. >>So in the business case I've written for the U. K's exa scale computer, I actually characterized this is a choice between the American model in the Japanese model. Okay, both of frozen, both of condoms. Eso in America, they're very much gone down the chorus plus GPU or GPU fruit. Um, so you might have, you know, an Intel Xeon or an M D process er center or unarmed process or, for that matter on you might have, you know, 24 g. P. U s. I think the most interesting thing that I've seen is definitely this move to a single address space. So the data that you have will be accessible, but the G p u on the CPU, I think you know, that's really bean. One of the key things that stopped the uptake of GPS today and that that that one single change is going Thio, I think, uh, make things very, very interesting. But I'm not entirely convinced that the CPU GPU model because I think that it's very difficult to get all the all the performance set of the GPU. You know, it will do well in H p l, for example, high performance impact benchmark we're discussing at the beginning of this interview. But in riel scientific workloads, you know, you still find it difficult to find all the performance that has promised. So, you know, the Japanese approach, which is the core, is only approach. E think it's very attractive, inasmuch as you know They're using very high bandwidth memory, very interesting process of which they are going to have to, you know, which they could develop together over 10 year period. And this is one thing that people don't realize the Japanese program and the American Mexico program has been working for 10 years on these systems. I think the Japanese process really interesting because, um, it when you look at the performance, it really does work for their scientific work clothes, and that's that does interest me a lot. This this combination of a A process are designed to do good science, high bandwidth memory and a real understanding of how data flows around the supercomputer. I think those are the things are exciting me at the moment. Obviously, you know, there's new networking technologies, I think, in the fullness of time, not necessarily for the first systems. You know, over the next decade we're going to see much, much more activity on silicon photonics. I think that's really, really fascinating all of these things. I think in some respects the last decade has just bean quite incremental improvements. But I think we're supercomputing is going in the moment. We're a very very disruptive moment again. That goes back to start this discussion. Why is extra skill been difficult to get? Thio? Actually, because the disruptive moment in technology. >>Professor Parsons, thank you very much for your time and your insights. Thank you. Pleasure and folks. Thank you for watching. I hope you've learned something, or at least enjoyed it. With that, I would ask you to stay safe and goodbye.

Published Date : Oct 16 2020

SUMMARY :

I am the director of HPC Strategic programs I suppose that the S I milestones of high performance computing's come and go, But looking at the X scale we're looking at, you know, four or five million cores on taming But you still you could have You could have bought one. challenges e think you know, we use quite arbitrary focus around exa scale is to look at, you know, new technologies, Well, I'm sure you don't tell me one, Ben. outside the door over there who would love to sell you one. So I think there's always a slight conceit when you buy a you know, the workloads. That's one of the major prizes in our area, you know, gets announced you know, the grand challenges of science, possibly to hide I think you know what I've seen over the last few years is a renaissance about is I've seen the vendors, all the vendors, you know, Inasmuch as you know, speaking for the UK, we put in place a rapid to currently enable, you know, I think you know, that's really bean. Professor Parsons, thank you very much for your time and your insights.

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Sanjay Poonen, VMware | VMworld 2020


 

>>from around the globe. It's the Cube with digital coverage of VM World 2020 brought to you by VM Ware and its ecosystem partners. Hello and welcome back to the cubes. Virtual coverage of VM World 2020 Virtual I'm John for your host of the Cube, our 11th year covering V emeralds. Not in person. It's virtual. I'm with my coast, Dave. A lot, of course. Ah, guest has been on every year since the cubes existed. Sanjay Putin, who is now the chief operating officer for VM Ware Sanjay, Great to see you. It's our 11th years. Virtual. We're not in person. Usually high five are going around. But hey, virtual fist pump, >>virtual pissed bump to you, John and Dave, always a pleasure to talk to you. I give you more than a virtual pistol. Here's a virtual hug. >>Well, so >>great. Back at great. >>Great to have you on. First of all, a lot more people attending the emerald this year because it's virtual again, it doesn't have the face to face. It is a community and technical events, so people do value that face to face. Um, but it is virtually a ton of content, great guests. You guys have a great program here, Very customer centric. Kind of. The theme is, you know, unpredictable future eyes is really what it's all about. We've talked about covert you've been on before. What's going on in your perspective? What's the theme of your main talks? >>Ah, yeah. Thank you, John. It's always a pleasure to talk to you folks. We we felt as we thought, about how we could make this content dynamic. We always want to make it fresh. You know, a virtual show of this kind and program of this kind. We all are becoming experts at many Ted talks or ESPN. Whatever your favorite program is 60 minutes on becoming digital producers of content. So it has to be crisp, and everybody I think was doing this has found ways by which you reduce the content. You know, Pat and I would have normally given 90 minute keynotes on day one and then 90 minutes again on day two. So 180 minutes worth of content were reduced that now into something that is that entire 180 minutes in something that is but 60 minutes. You you get a chance to use as you've seen from the keynote an incredible, incredible, you know, packed array of both announcements from Pat myself. So we really thought about how we could organize this in a way where the content was clear, crisp and compelling. Thekla's piece of it needed also be concise, but then supplemented with hundreds of sessions that were as often as possible, made it a goal that if you're gonna do a break out session that has to be incorporate or lead with the customer, so you'll see not just that we have some incredible sea level speakers from customers that have featured in in our pattern, Mikey notes like John Donahoe, CEO of Nike or Lorry beer C I, a global sea of JPMorgan Chase partner Baba, who is CEO of Zuma Jensen Wang, who is CEO of video. Incredible people. Then we also had some luminaries. We're gonna be talking in our vision track people like in the annuity. I mean, one of the most powerful women the world many years ranked by Fortune magazine, chairman, CEO Pepsi or Bryan Stevenson, the person who start in just mercy. If you watch that movie, he's a really key fighter for social justice and criminal. You know, reform and jails and the incarceration systems. And Malala made an appearance. Do I asked her personally, I got to know her and her dad's and she spoke two years ago. I asked her toe making appearance with us. So it's a really, really exciting until we get to do some creative stuff in terms of digital content this year. >>So on the product side and the momentum side, you have great decisions you guys have made in the past. We covered that with Pat Gelsinger, but the business performance has been very strong with VM. Where, uh, props to you guys, Where does this all tie together for in your mind? Because you have the transformation going on in a highly accelerated rate. You know, cov were not in person, but Cove in 19 has proven, uh, customers that they have to move faster. It's a highly accelerated world, a lot. Lots changing. Multi cloud has been on the radar. You got security. All the things you guys are doing, you got the AI announcements that have been pumping. Thean video thing was pretty solid. That project Monterey. What does the customer walk away from this year and and with VM where? What is the main theme? What what's their call to action? What's what do they need to be doing? >>I think there's sort of three things we would encourage customers to really think about. Number one is, as they think about everything in infrastructure, serves APS as they think about their APS. We want them to really push the frontier of how they modernize their athletic applications. And we think that whole initiative off how you modernized applications driven by containers. You know, 20 years ago when I was a developer coming out of college C, C plus, plus Java and then emerge, these companies have worked on J two ee frameworks. Web Logic, Be Aware logic and IBM Web Street. It made the development off. Whatever is e commerce applications of portals? Whatever was in the late nineties, early two thousands much, much easier. That entire world has gotten even easier and much more Micro service based now with containers. We've been talking about kubernetes for a while, but now we've become the leading enterprise, contain a platform making some incredible investments, but we want to not just broaden this platform. We simplified. It is You've heard everything in the end. What works in threes, right? It's sort of like almost t shirt sizing small, medium, large. So we now have tens Ooh, in the standard. The advanced the enterprise editions with lots of packaging behind that. That makes it a very broad and deep platform. We also have a basic version of it. So in some sense it's sort of like an extra small. In addition to the small medium large so tends to and everything around at modernization, I think would be message number one number two alongside modernization. You're also thinking about migration of your workloads and the breadth and depth of, um, er Cloud Foundation now of being able to really solve, not just use cases, you are traditionally done, but also new ai use cases. Was the reason Jensen and us kind of partner that, and I mean what a great company and video has become. You know, the king maker of these ai driven applications? Why not run those AI applications on the best infrastructure on the planet? Remember, that's a coming together of both of our platforms to help customers. You know automotive banking fraud detection is a number of AI use cases that now get our best and we want it. And the same thing then applies to Project Monterey, which takes the B c f e m A Cloud Foundation proposition to smart Knicks on Dell, HP Lenovo are embracing the in video Intel's and Pen Sandoz in that smart make architectural, however, that so that entire world of multi cloud being operative Phobia Macleod Foundation on Prem and all of its extended use cases like AI or Smart Knicks or Edge, but then also into the AWS Azure, Google Multi Cloud world. We obviously had a preferred relationship with Amazon that's going incredibly well, but you also saw some announcements last week from, uh, Microsoft Azure about azure BMR solutions at their conference ignite. So we feel very good about the migration opportunity alongside of modernization on the third priority, gentlemen would be security. It's obviously a topic that I most recently taken uninterested in my day job is CEO of the company running the front office customer facing revenue functions by night job by Joe Coffin has been driving. The security strategy for the company has been incredibly enlightening to talk, to see SOS and drive this intrinsic security or zero trust from the network to end point and workload and cloud security. And we made some exciting announcements there around bringing together MAWR capabilities with NSX and Z scaler and a problem black and workload security. And of course, Lassiter wouldn't cover all of this. But I would say if I was a attendee of the conference those the three things I want them to take away what BMR is doing in the future of APS what you're doing, the future of a multi cloud world and how we're making security relevant for distributed workforce. >>I know David >>so much to talk about here, Sanjay. So, uh, talk about modern APS? That's one of the five franchise platforms VM Ware has a history of going from, you know, Challenger toe dominant player. You saw that with end user computing, and there's many, many other examples, so you are clearly one of the top, you know. Let's call it five or six platforms out there. We know what those are, uh, and but critical to that modern APS. Focus is developers, and I think it's fair to say that that's not your wheelhouse today, but you're making moves there. You agree that that is, that is a critical part of modern APS, and you update us on what you're doing for that community to really take a leadership position there. >>Yeah, no, I think it's a very good point, David. We way seek to constantly say humble and hungry. There's never any assumption from us that VM Ware is completely earned anyplace off rightful leadership until we get thousands, tens of thousands. You know, we have a half a million customers running on our virtualization sets of products that have made us successful for 20 years 70 million virtual machines. But we have toe earn that right and containers, and I think there will be probably 10 times as many containers is their virtual machines. So if it took us 20 years to not just become the leader in in virtual machines but have 70 million virtual machines, I don't think it will be 20 years before there's a billion containers and we seek to be the leader in that platform. Now, why, Why VM Where and why do you think we can win in their long term. What are we doing with developers Number one? We do think there is a container capability independent of virtual machine. And that's what you know, this entire world of what hefty on pivotal brought to us on. You know, many of the hundreds of customers that are using what was formerly pivotal and FDR now what's called Tan Xue have I mean the the case. Studies of what those customers are doing are absolutely incredible. When I listen to them, you take Dick's sporting goods. I mean, they are building curbside, pick up a lot of the world. Now the pandemic is doing e commerce and curbside pick up people are going to the store, That's all based on Tan Xue. We've had companies within this sort of world of pandemic working on contact, tracing app. Some of the diagnostic tools built without they were the lab services and on the 10 zoo platform banks. Large banks are increasingly standardizing on a lot of their consumer facing or wealth management type of applications, anything that they're building rapidly on this container platform. So it's incredible the use cases I'm hearing public sector. The U. S. Air Force was talking about how they've done this. Many of them are not public about how they're modernizing dams, and I tend to learn the best from these vertical use case studies. I mean, I spend a significant part of my life is you know, it s a P and increasingly I want to help the company become a lot more vertical. Use case in banking, public sector, telco manufacturing, CPG retail top four or five where we're seeing a lot of recurrence of these. The Tan Xue portfolio actually brings us closest to almost that s a P type of dialogue because we're having an apse dialogue in the in the speak of an industry as opposed to bits and bytes Notice I haven't talked at all about kubernetes or containers. I'm talking about the business problem being solved in a retailer or a bank or public sector or whatever have you now from a developer audience, which was the second part of your question? Dave, you know, we talked about this, I think a year or two ago. We have five million developers today that we've been able to, you know, as bringing these acquisitions earn some audience with about two or three million from from the spring community and two or three million from the economic community. So think of those five million people who don't know us because of two acquisitions we don't. Obviously spring was inside Vienna where went out of pivotal and then came back. So we really have spent a lot of time with that community. A few weeks ago, we had spring one. You guys are aware of that? That conference record number of attendees okay, Registered, I think of all 40 or 50,000, which is, you know, much bigger than the physical event. And then a substantial number of them attended live physical. So we saw a great momentum out of spring one, and we're really going to take care of that, That that community base of developers as they care about Java Manami also doing really, really well. But then I think the rial audience it now has to come from us becoming part of the conversation. That coupon at AWS re invent at ignite not just the world, I mean via world is not gonna be the only place where infrastructure and developers come to. We're gonna have to be at other events which are very prominent and then have a developer marketplace. So it's gonna be a multiyear effort. We're okay with that. To grow that group of about five million developers that we today Kate or two on then I think there will be three or four other companies that also play very prominently to developers AWS, Microsoft and Google. And if we're one among those three or four companies and remembers including that list, we feel very good about our ability to be in a place where this is a shared community, takes a village to approach and an appeal to those developers. I think there will be one of those four companies that's doing this for many years to >>come. Santa, I got to get your take on. I love your reference to the Web days and how the development environment change and how the simplicity came along very relevant to how we're seeing this digital transformation. But I want to get your thoughts on how you guys were doing pre and now during and Post Cove it. You already had a complicated thing coming on. You had multi cloud. You guys were expanding your into end you had acquisitions, you mentioned a few of them. And then cove it hit. Okay, so now you have Everything is changing you got. He's got more complex city. You have more solutions, and then the customer psychology is change. You got to spectrums of customers, people trying to save their business because it's changed, their customer behavior has changed. And you have other customers that are doubling down because they have a tailwind from Cove it, whether it's a modern app, you know, coming like Zoom and others are doing well because of the environment. So you got your customers air in this in this in this, in this storm, you know, they're trying to save down, modernized or or or go faster. How are you guys changing? Because it's impacted how you sell. People are selling differently, how you implement and how you support customers, because you already had kind of the whole multi cloud going on with the modern APS. I get that, but Cove, it has changed things. How are you guys adopting and changing to meet the customer needs who are just trying to save their business on re factor or double down and continue >>John. Great question. I think I also talked about some of this in one of your previous digital events that you and I talked about. I mean, you go back to the last week of February 1st week of March, actually back up, even in January, my last trip on a plane. Ah, major trip outside this country was the World Economic Forum in Davos. And, you know, there were thousands of us packed into the small digits in Switzerland. I was sitting having dinner with Andy Jassy in a restaurant one night that day. Little did we know. A month later, everything would change on DWhite. We began to do in late February. Early March was first. Take care of employees. You always wanna have the pulse, check employees and be in touch with them. Because the health and safety of employees is much more important than the profits of, um, where you know. So we took care of that. Make sure that folks were taking care of older parents were in good place. We fortunately not lost anyone to death. Covert. We had some covert cases, but they've recovered on. This is an incredible pandemic that connects all of us in the human fabric. It has no separation off skin color or ethnicity or gender, a little bit of difference in people who are older, who might be more affected or prone to it. But we just have to, and it's taught me to be a significantly more empathetic. I began to do certain things that I didn't do before, but I felt was the right thing to do. For example, I've begun to do 25 30 minute calls with every one of my key countries. You know, as I know you, I run customer operations, all of the go to market field teams reporting to me on. I felt it was important for me to be showing up, not just in the big company meetings. We do that and big town halls where you know, some fractions. 30,000 people of VM ware attend, but, you know, go on, do a town hall for everybody in a virtual zoom session in Japan. But in their time zone. So 10 o'clock my time in the night, uh, then do one in China and Australia kind of almost travel around the world virtually, and it's not long calls 25 30 minutes, where 1st 10 or 15 minutes I'm sharing with them what I'm seeing across other countries, the world encouraging them to focus on a few priorities, which I'll talk about in a second and then listening to them for 10 15 minutes and be, uh and then the call on time or maybe even a little earlier, because every one of us is going to resume button going from call to call the call. We're tired of T. There's also mental, you know, fatigue that we've gotta worry about. Mental well, being long term. So that's one that I personally began to change. I began to also get energy because in the past, you know, I would travel to Europe or Asia. You know, 40 50%. My life has travel. It takes a day out of your life on either end, your jet lag. And then even when you get to a Tokyo or Beijing or to Bangalore or the London, getting between sites of these customers is like a 45 minute, sometimes in our commute. Now I'm able to do many of these 25 30 minute call, so I set myself a goal to talk to 1000 chief security officers. I know a lot of CEOs and CFOs from my times at S A P and VM ware, but I didn't know many security officers who often either work for a CEO or report directly to the legal counsel on accountable to the audit committee of the board. And I got a list of these 1,002,000 people we called email them. Man, I gotta tell you, people willing to talk to me just coming, you know, into this I'm about 500 into that. And it was role modeling to my teams that the top of the company is willing to spend as much time as possible. And I have probably gotten a lot more productive in customer conversations now than ever before. And then the final piece of your question, which is what do we tell the customer in terms about portfolio? So these were just more the practices that I was able to adapt during this time that have given me energy on dial, kind of get scared of two things from the portfolio perspective. I think we began to don't notice two things. One is Theo entire move of migration and modernization around the cloud. I describe that as you know, for example, moving to Amazon is a migration opportunity to azure modernization. Is that whole Tan Xue Eminem? Migration of modernization is highly relevant right now. In fact, taking more speed data center spending might be on hold on freeze as people kind of holding till depend, emmick or the GDP recovers. But migration of modernization is accelerating, so we wanna accelerate that part of our portfolio. One of the products we have a cloud on Amazon or Cloud Health or Tan Xue and maybe the other offerings for the other public dog. The second part about portfolio that we're seeing acceleration around is distributed workforce security work from home work from anywhere. And that's that combination off workspace, one for both endpoint management, virtual desktops, common black envelope loud and the announcements we've now made with Z scaler for, uh, distributed work for security or what the analysts called secure access. So message. That's beautiful because everyone working from home, even if they come back to the office, needs a very different model of security and were now becoming a leader in that area. of security. So these two parts of the portfolio you take the five franchise pillars and put them into these two buckets. We began to see momentum. And the final thing, I would say, Guys, just on a soft note. You know, I've had to just think about ways in which I balance work and family. It's just really easy. You know what, 67 months into this pandemic to burn out? Ah, now I've encouraged my team. We've got to think about this as a marathon, not a sprint. Do the personal things that you wanna do that will make your life better through this pandemic. That in practice is that you keep after it. I'll give you one example. I began biking with my kids and during the summer months were able to bike later. Even now in the fall, we're able to do that often, and I hope that's a practice I'm able to do much more often, even after the pandemic. So develop some activities with your family or with the people that you love the most that are seeing you a lot more and hopefully enjoying that time with them that you will keep even after this pandemic ends. >>So, Sanjay, I love that you're spending all this time with CSOs. I mean, I have a Well, maybe not not 1000 but dozens. And they're such smart people. They're really, you know, in the thick of things you mentioned, you know, your partnership with the scale ahead. Scott Stricklin on who is the C. C so of Wyndham? He was talking about the security club. But since the pandemic, there's really three waves. There's the cloud security, the identity, access management and endpoint security. And one of the things that CSOs will tell you is the lack of talent is their biggest challenge. And they're drowning in all these products. And so how should we think about your approach to security and potentially simplifying their lives? >>Yeah. You know, Dave, we talked about this, I think last year, maybe the year before, and what we were trying to do in security was really simplified because the security industry is like 5000 vendors, and it's like, you know, going to a doctor and she tells you to stay healthy. You gotta have 5000 tablets. You just cannot eat that many tablets you take you days, weeks, maybe a month to eat that many tablets. So ah, grand simplification has to happen where that health becomes part of your diet. You eat your proteins and vegetables, you drink your water, do your exercise. And the analogy and security is we cannot deploy dozens of agents and hundreds of alerts and many, many consoles. Uh, infrastructure players like us that have control points. We have 70 million virtual machines. We have 75 million virtual switches. We have, you know, tens of million's off workspace, one of carbon black endpoints that we manage and secure its incumbent enough to take security and making a lot more part of the infrastructure. Reduce the need for dozens and dozens of point tools. And with that comes a grand simplification of both the labor involved in learning all these tools. Andi, eventually also the cost of ownership off those particular tool. So that's one other thing we're seeking to do is increasingly be apart off that education off security professionals were both investing in ah, lot of off, you know, kind of threat protection research on many of our folks you know who are in a threat. Behavioral analytics, you know, kind of thread research. And people have come out of deep hacking experience with the government and others give back to the community and teaching classes. Um, in universities, there are a couple of non profits that are really investing in security, transfer education off CSOs and their teams were contributing to that from the standpoint off the ways in which we can give back both in time talent and also a treasure. So I think is we think about this. You're going to see us making this a long term play. We have a billion dollar security business today. There's not many companies that have, you know, a billion dollar plus of security is probably just two or three, and some of them have hit a wall in terms of their progress sport. We want to be one of the leaders in cybersecurity, and we think we need to do this both in building great product satisfying customers. But then also investing in the learning, the training enable remember, one of the things of B M worlds bright is thes hands on labs and all the training enable that happened at this event. So we will use both our platform. We in world in a variety of about the virtual environments to ensure that we get the best education of security to professional. >>So >>that's gonna be exciting, Because if you look at some of the evaluations of some of the pure plays I mean, you're a cloud security business growing a triple digits and, you know, you see some of these guys with, you know, $30 billion valuations, But I wanted to ask you about the market, E v m. Where used to be so simple Right now, you guys have expanded your tam dramatically. How are you thinking about, you know, the market opportunity? You've got your five franchise platforms. I know you're very disciplined about identifying markets, and then, you know, saying, Okay, now we're gonna go compete. But how do you look at the market and the market data? Give us the update there. >>Yeah, I think. Dave, listen, you know, I like davinci statement. You know, simplicity is the greatest form of sophistication, and I think you've touched on something that which is cos we get bigger. You know, I've had the great privilege of working for two great companies. s a P and B M where the bulk of my last 15 plus years And if something I've learned, you know, it's very easy. Both companies was to throw these TLS three letter acronyms, okay? And I use an acronym and describing the three letter acronyms like er or s ex. I mean, they're all acronyms and a new employee who comes to this company. You know, Carol Property, for example. We just hired her from Google. Is our CMO her first comments like, My goodness, there is a lot of off acronyms here. I've gotta you need a glossary? I had the same reaction when I joined B. M or seven years ago and had the same reaction when I joined the S A. P 15 years ago. Now, of course, two or three years into it, you learn everything and it becomes part of your speed. We have toe constantly. It's like an accordion like you expanded by making it mawr of luminous and deep. But as you do that it gets complex, you then have to simplify it. And that's the job of all of us leaders and I this year, just exemplifying that I don't have it perfect. One of the gifts I do have this communication being able to simplify things. I recorded a five minute video off our five franchise pill. It's just so that the casual person didn't know VM where it could understand on. Then, when I'm on your shore and when on with Jim Cramer and CNBC, I try to simplify, simplify, simplify, simplify because the more you can talk and analogies and pictures, the more the casual user. I mean, of course, and some other audiences. I'm talking to investors. Get it on. Then, Of course, as you go deeper, it should be like progressive layers or feeling of an onion. You can get deeper. It's not like the entire discussion with Sanjay Putin on my team is like, you know, empty suit. It's a superficial discussion. We could go deeper, but you don't have to begin the discussion in the bowels off that, and that's really what we don't do. And then the other part of your question was, how do we think about new markets? You know, we always start with Listen, you sort of core in contact our borough come sort of Jeffrey Moore, Andi in the Jeffrey more context. You think about things that you do really well and then ask yourself outside of that what the Jason sees that are closest to you, that your customers are asking you to advance into on that, either organically to partnerships or through acquisitions. I think John and I talked about in the previous dialogue about the framework of build partner and by, and we always think about it in that order. Where do we advance and any of the moves we've made six years ago, seven years ago and I joined the I felt VM are needed to make a move into mobile to really cement opposition in end user computing. And it took me some time to convince my peers and then the board that we should by Air One, which at that time was the biggest acquisition we've ever done. Okay. Similarly, I'm sure prior to me about Joe Tucci, Pat Nelson. We're thinking about nice here, and I'm moving to networking. Those were too big, inorganic moves. +78 years of Raghu was very involved in that. The decisions we moved to the make the move in the public cloud myself. Rgu pack very involved in the decision. Their toe partner with Amazon, the change and divest be cloud air and then invested in organic effort around what's become the Claudia. That's an organic effort that was an acquisition fast forward to last year. It took me a while to really Are you internally convinced people and then make the move off the second biggest acquisition we made in carbon black and endpoint security cement the security story that we're talking about? Rgu did a similar piece of good work around ad monetization to justify that pivotal needed to come back in. So but you could see all these pieces being adjacent to the core, right? And then you ask yourself, Is that context meaning we could leave it to a partner like you don't see us get into the hardware game we're partnering with. Obviously, the players like Dell and HP, Lenovo and the smart Knick players like Intel in video. In Pensando, you see that as part of the Project Monterey announcement. But the adjacent seas, for example, last year into app modernization up the stack and into security, which I'd say Maura's adjacent horizontal to us. We're now made a lot more logical. And as we then convince ourselves that we could do it, convince our board, make the move, We then have to go and tell our customers. Right? And this entire effort of talking to CSOs What am I doing is doing the same thing that I did to my board last year, simplified to 15 minutes and get thousands of them to understand it. Received feedback, improve it, invest further. And actually, some of the moves were now making this year around our partnership in distributed Workforce Security and Cloud Security and Z scaler. What we're announcing an XDR and Security Analytics. All of the big announcements of security of this conference came from what we heard last year between the last 12 months of my last year. Well, you know, keynote around security, and now, and I predict next year it'll be even further. That's how you advance the puck every year. >>Sanjay, I want to get your thoughts. So now we have a couple minutes left. But we did pull the audience and the community to get some questions for you, since it's virtually wanted to get some representation there. So I got three questions for you. First question, what comes after Cloud and number two is VM Ware security company. And three. What company had you wish you had acquired? >>Oh, my goodness. Okay, the third one eyes gonna be the turkey is one, I think. Listen, because I'm gonna give you my personal opinion, and some of it was probably predates me, so I could probably safely So do that. And maybe put the blame on Joe Tucci or somebody else is no longer here. But let me kind of give you the first two. What comes after cloud? I think clouds gonna be with us for a long time. First off this multi cloud world, you just look at the moment, um, that AWS and azure and the other clouds all have. It's incredible on I think this that multi cloud from phenomenon. But if there's an adapt ation of it, it's gonna be three forms of cloud. People are really only focus today in private public cloud. You have to remember the edge and Telco Cloud and this pendulum off the right balance of workloads between the data center called it a private cloud. The public cloud on one end and the telco edge on the other end. I think we're in a really good position for workloads to really swing between all three of those locations. Three other part that I think comes as a sequel to Cloud is cloud native. All of the capabilities a serverless functions but also containers that you know. Obviously the one could think of that a sister topics to cloud but the entire world of containers. The other seat, uh, then cloud a cloud native will also be topics, but these were all fairly connected. That's how I'd answer the first question. A security company? Absolutely. We you know, we aspire to be one of the leading companies in cyber security. I don't think they will be only one. We have to show this by the wealth on breath of our customers. The revenue momentum we have Gartner ranking us or the analysts ranking us in top rights of magic quadrants being viewed as an innovator simplifying the stack. But listen, we weren't even on the radar. We weren't speaking of the security conferences years ago. Now we are. We have a billion dollar security business, 20,000 plus customers, really strong presences and network endpoint and workload and Cloud Security. The three Coppola's a lot more coming in Security analytics, Cloud Security distributed workforce Security. So we're here to stay. And if anything, BMR persist through this, we're planning for multi your five or 10 year timeframe. And in that course I mean, the competition is smaller. Companies that don't have the breadth and depth of the n words are Andy muscle and are going market. We just have to keep building great products and serving customer on the third man. There's so many. But I mean, I think Listen, when I was looking back, I always wondered this is before I joined so I could say the summit speculatively on. Don't you know, make this This is BMR. Sorry. This is Sanjay one's opinion. Not VM. I gotta make very, very clear. Well, listen, I would have if I was at BMO in 2012 or 2013. I would love to about service now then service. It was a great company. I don't even know maybe the company's talk, but then talk about a very successful company at that time now. Maybe their priorities were different. I wasn't at the company at the time, but I can speculate if that had happened, that would have been an interesting Now I think that was during the time of Paul Maritz here and and so on. So for them, maybe there were other priorities the company need to get done. But at that time, of course, today s so it's not as big of a even slightly bigger market cap than us. So that's not happening. But that's a great example of a good company that I think would have at that time fit very well with VM Ware. And then there's probably we don't look back and regret we move forward. I mean, I think about the acquisitions we have made the big ones. Okay, Nice era air watch pop in black. Pivotal. The big moves we've made in terms of partnership. Amazon. What? We're announcing this This, you know, this week within video and Z scaler. So you never look back and regret. You always look for >>follow up on that To follow up on that from a developer, entrepreneurial or partner Perspective. Can you share where the white spaces for people to innovate around vm Where where where can people partner and play. Whether I'm an entrepreneur in a garage or venture back, funded or say a partner pivoting and or resetting with Govind, where's the white spaces with them? >>I think that, you know, there's gonna be a number off places where the Tan Xue platform develops, as it kind of makes it relevant to developers. I mean, there's, I think the first way we think about this is to make ourselves relevant toe all of that ecosystem around the C I. C. D type apply platform. They're really good partners of ours. They're like, get lab, You know, all of the ways in which open source communities, you know will play alongside that Hash E Corp. Jay frog there number of these companies that are partnering with us and we're excited about all of their relevancy to tend to, and it's our job to go and make that marketplace better and better. You're going to hear more about that coming up from us on. Then there's the set of data companies, you know, con fluent. You know, of course, you've seen a big I p o of a snowflake. All of those data companies, we'll need a very natural synergy. If you think about the old days of middleware, middleware is always sort of separate from the database. I think that's starting to kind of coalesce. And Data and analytics placed on top of the modern day middleware, which is containers I think it's gonna be now does VM or play physically is a data company. We don't know today we're gonna partner very heavily. But picking the right set of partners been fluent is a good example of one on. There's many of the next generation database companies that you're going to see us partner with that will become part of that marketplace influence. And I think, as you see us certainly produce out the VM Ware marketplace for developers. I think this is gonna be a game changing opportunity for us to really take those five million developers and work with the leading companies. You know, I use the example of get Lab is an example get help there. Others that appeal to developers tie them into our developer framework. The one thing you learn about developers, you can't have a mindset. With that, you all come to just us. It's a very mingled village off multiple ecosystems and Venn diagrams that are coalescing. If you try to take over the world, the developer community just basically shuns you. You have to have a very vibrant way in which you are mingling, which is why I described. It's like, Listen, we want our developers to come to our conferences and reinvent and ignite and get the best experience of all those provide tools that coincide with everybody. You have to take a holistic view of this on if you do that over many years, just like the security topic. This is a multi year pursuit for us to be relevant. Developers. We feel good about the future being bright. >>David got five minutes e. >>I thought you were gonna say Zoom, Sanjay, that was That was my wildcard. >>Well, listen, you know, I think it was more recently and very fast catapult Thio success, and I don't know that that's clearly in the complete, you know, sweet spot of the anywhere. I mean, you know, unified collaboration would have probably put us in much more competition with teams and, well, back someone you always have to think about what's in the in the bailiwick of what's closest to us, but zooms a great partner. Uh, I mean, obviously you love to acquire anybody that's hot, but Eric's doing really well. I mean, Erica, I'm sure he had many people try to come to buy him. I'm just so proud of him as a friend of all that he was named to Time magazine Top 100. But what he's done is phenomenon. I think he could build a company that's just his important, his Facebook. So, you know, I encourage him. Don't sell, keep building the company and you'll build a company that's going to be, you know, the enterprise version of Facebook. And I think that's a tremendous opportunity to do this better than anybody else is doing. And you know, I'm as an immigrant. He's, you know, China. Born now American, I'm Indian born, American, assim immigrants. We both have a similar story. I learned a lot from him. I learned a lot from him, from on speed on speed and how to move fast, he tells me he learns a thing to do for me on scale. We teach each other. It's a beautiful friendship. >>We'll make sure you put in a good word for the Kiwi. One more zoom integration >>for a final word or the zoom that is the future Facebook of the enterprise. Whatever, Sanjay, Thank >>you for connecting with us. Virtually. It is a digital foundation. It is an unpredictable world. Um, it's gonna change. It could be software to find the operating models or changing you guys. We're changing how you serve customers with new chief up commercial customer officer you have in place, which is a new hire. Congratulations. And you guys were flexing with the market and you got a tailwind. So congratulations, >>John and Dave. Always a pleasure. We couldn't do this without the partnership. Also with you. Congratulations of Successful Cube. And in its new digital format, Thank you for being with us With VM world here on. Do you know all that you're doing to get the story out? The guests that you have on the show, they look forward, including the nonviable people like, Hey, can I get on the Cuban like, Absolutely. Because they look at your platform is away. I'm telling this story. Thanks for all you're doing. I wish you health and safety. >>I'm gonna bring more community. And Dave is, you know, and Sanjay, and it's easier without the travel. Get more interviews, tell more stories and tell the most important stories. And thank you for telling your story and VM World story here of the emerald 2020. Sanjay Poon in the chief operating officer here on the Cube I'm John for a day Volonte. Thanks for watching Cube Virtual. Thanks for watching.

Published Date : Sep 30 2020

SUMMARY :

World 2020 brought to you by VM Ware and its ecosystem partners. I give you more than a virtual pistol. Back at great. Great to have you on. I mean, one of the most powerful women the world many years ranked by Fortune magazine, chairman, CEO Pepsi or So on the product side and the momentum side, you have great decisions you guys have made in the past. And the same thing then applies to Project Monterey, many other examples, so you are clearly one of the top, you know. And that's what you know, this entire world of what hefty on pivotal brought to us on. So you got your customers air in this in this in this, in this storm, I began to also get energy because in the past, you know, I would travel to Europe or Asia. They're really, you know, in the thick of things you mentioned, you know, your partnership with the scale ahead. You just cannot eat that many tablets you take you days, weeks, maybe a month to eat that many tablets. you know, the market opportunity? You know, we always start with Listen, you sort of core in contact our What company had you But let me kind of give you the first two. Can you share where the white spaces for people to innovate around vm You have to have a very vibrant way in which you are mingling, success, and I don't know that that's clearly in the complete, you know, We'll make sure you put in a good word for the Kiwi. is the future Facebook of the enterprise. It could be software to find the operating models or changing you guys. The guests that you have on the show, And Dave is, you know, and Sanjay, and it's easier without the travel.

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Brad Myles, Polaris | AWS Imagine Nonprofit 2019


 

>> Announcer: From Seattle, Washington, it's theCUBE! Covering AWS IMAGINE Nonprofit. Brought to you by Amazon Web Services. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're in the waterfront in Seattle, Washington, it's absolutely gorgeous here the last couple of days. We're here for the AWS IMAGINE Nonprofit event. We were here a couple weeks ago for the education event, now they have a whole separate track for nonprofits, and what's really cool about nonprofits is these people, these companies are attacking very, very big, ugly problems. It's not advertising, it's not click here and get something, these are big things, and one of the biggest issues is human trafficking. You probably hear a lot about it, it's way bigger than I ever thought it was, and we're really excited to have an expert in the field that, again, is using the power of AWS technology as well as their organization to help fight this cause. And we're excited to have Brad Myles, he is the CEO of Polaris and just coming off a keynote, we're hearing all about your keynote. So Brad, first off, welcome. >> Yeah, well thank you, thank you for having me. >> Absolutely, so Polaris, give us a little bit about kind of what's the mission for people that aren't familiar with the company. >> Yeah, so Polaris, we are a nonprofit that works full-time on this issue. We both combat the issue and try to get to long-term solutions, and respond to the issue and restore freedom to survivors by operating the National Human Trafficking Hotline for the United States, so, it's part kind of big data and long-term solutions, and it's part responding to day-to-day cases that break across the country every day. >> Right, in preparing for this interview and spending some time on the site there was just some amazing things that just jump right off the page. 24.9 million people are involved in this. Is that just domestically here in the States, or is that globally? >> That's a global number. So when you're thinking about human trafficking, think about three buckets. The first bucket is any child, 17 or younger, being exploited in the commercial sex trade. The second bucket is any adult, 18 or over, who's in the sex trade by force, fraud, or coercion. And the third bucket is anyone forced to work in some sort of other labor or service industry by force, fraud, or coercion. So you've got the child sex trafficking bucket, you've got the adult sex trafficking bucket, and then you've got all the labor trafficking bucket, right? You add up those three buckets globally, that's the number that the International Labour Organization came out and said 25 million around the world are those three buckets in a given year. >> Right, and I think again, going through the website, some of the just crazy discoveries, it's the child sex trafficking you can kind of understand that that's part of the problem, the adult sex trafficking. But you had like 25 different human trafficking business models, I forget the term that was used, for a whole host of things well beyond just the sex trade. It's a very big and unfortunately mature industry. >> Totally, yeah, so we, so the first thing that we do that we're kind of known for is operating the National Human Trafficking Hotline. The National Human Trafficking Hotline leads to having a giant data set on trafficking, it's 50,000 cases of trafficking that we've worked on. So then we analyzed that data set and came to the breakthrough conclusion that there are these 25 major forms, and almost any single call that we get in to the National Hotline is going to be one of those 25 types. And once you know that then the problem doesn't seem so overwhelming, it's not, you know, thousands of different types, it's these 25 things, so, it's 18 labor trafficking types and seven sex trafficking types. And it enables a little bit more granular analysis than just saying sex trafficking or labor trafficking which is kind of too broad and general. Let's get really specific about it, we're talking about these late night janitors, or we're talking about these people in agriculture, or we're talking about these women in illicit massage businesses. It enables the conversation to get more focused. >> Right, it's so interesting right, that's such a big piece of the big data trend that we see all over the place, right? It used to be, you know, you had old data, a sample of old data that you took an aggregate of and worked off the averages. And now, because of big data, and the other tools that we have today, now actually you can work on individual cases. So as you look at it from a kind of a big data point of view, what are some of the things that you're able to do? And that lead directly to, everyone's talking about the presentation that you just got off of, in terms of training people to look for specific behaviors that fit the patterns, so you can start to break some of these cases. >> Exactly, so, I think that the human trafficking field risks being too generic. So if you're just saying to the populace, "Look for trafficking, look for someone who's scared." People are like, that's not enough, that's too vague, it's kind of slipping through my fingers. But if you say, "In this particular type of trafficking, "with traveling magazine sales crews, "if someone comes to your door "trying to sell you a magazine with these specific signs." So now instead of talking about general red flag indicators across all 25 types, we're coming up with red flag indicators for each of the 25 types. So instead of speaking in aggregate we're getting really specific, it's almost like specific gene therapy. And the data analysis on our data set is enabling that to happen, which makes the trafficking field smarter, we could get smarter about where victims are recruited from, we could get smarter about intervention points, and we could get smarter about where survivors might have a moment to kind of get help and get out. >> Right, so I got to dig into the magazine salesperson, 'cause I think we've all had the kid-- >> Brad: Have you had a kid come to you yet? >> Absolutely, and you know, you think first they're hustlin' but their papers are kind of torn up, and they've got their little certificate, certification. How does that business model work? >> Yeah, so that's one of the 25 types, they're called mag crews. There was a New York Times article written by a journalist named Ian Urbina who really studied this and it came out a number of years ago. Then they made a movie about it called "American Honey," if you watch with a number of stars. But essentially this is a very long-standing business model, it goes back 30 or 40 years of like the door-to-door salesperson, and like trying to win sympathy from people going to door-to-door sales. And then these kind of predatory groups decided to prey on disaffected U.S. citizen youth that are kind of bored, or are kind of working a low-wage job. And so they go up to these kids and they say, "Tired of working at the Waffle House? "Well why don't you join our crew and travel the country, "and party every night, and you'll be outdoors every day, "and it's coed, you get to hang out with girls, "you get to hang out with guys, "we'll drink every night and all you have to do "is sell magazines during the day." And it's kind of this alluring pitch, and then the crews turn violent, and there's sometimes quotas on the crew, there's sometimes coercion on the crew. We get a lot of calls from kids who are abandoned by the crew. Where the crew says, "If you act up "or if you don't adhere to our rules, "we'll just drive away and leave you in this city." >> Wherever. >> Is the crews are very mobile they have this whole language, they call it kind of jumping territory. So they'll drive from like Kansas City to a nearby state, and we'll get this call from this kid, they're like, "I'm totally homeless, my crew just left me behind "because I kind of didn't obey one of the rules." So a lot of people, when they think of human trafficking they're not thinking of like U.S. citizen kids knocking on your door. And we're not saying that every single magazine crew is human trafficking, but we are saying that if there's force, and coercion, and fraud, and lies, and people feel like they can't leave, and people feel like they're being coerced to work, this is actually a form of human trafficking of U.S. citizen youth which is not very well-known but we hear about it on the Hotline quite a lot. >> Right, so then I wonder if you could tell us more about the Delta story 'cause most of the people that are going to be watching this interview weren't here today to hear your keynote. So I wonder if you can explain kind of that whole process where you identified a specific situation, you train people that are in a position to make a difference and in fact they're making a big difference. >> Yeah. So the first big report that we released based on the Hotline data was the 25 types, right? We decided to do a followup to that called Intersections, where we reached out to survivors of trafficking and we said, "Can you tell us about "the legitimate businesses that your trafficker used "while you were being trafficked?" And all these survivors were like, "Yeah, sure, "we'll tell you about social media, "we'll tell you about transportation, "we'll tell you about banks, "we'll tell you about hotels." And so we then identified these six major industries that traffickers use that are using legitimate companies, like rental car companies, and airlines, and ridesharing companies. So then we reached out to a number of those corporate partners and said, "You don't want this stuff on your services, right?" And Delta really just jumped at this, they were just like, "We take this incredibly seriously. "We want our whole workforce trained. "We don't want any trafficker to feel like "they can kind of get away with it on our flights. "We want to be a leader in transportation." And then they began taking all these steps. Their CEO, Ed Bastian, took it very seriously. They launched a whole corporate-wide taskforce across departments, they hosted listening sessions with survivor leaders so survivors could coach them, and then they started launching this whole strategy around training their flight attendants, and then training their whole workforce, and then supporting the National Human Trafficking Hotline, they made some monetary donations to Polaris. We get situations on the Hotline where someone is in a dangerous situation and needs to be flown across the country, like an escape flight almost, and Delta donated SkyMiles for us to give to survivors who are trying to flee a situation, who needs a flight. They can go to an airport and get on a flight for free that will fly them across the country. So it's almost like a modern day Underground Railroad, kind of flying people on planes. >> Jeff: Right, right. >> So they've just been an amazing partner, and they even then took the bold step of saying, "Well let's air a PSA on our flights "so the customer base can see this." So when you're on a Delta flight you'll see this PSA about human trafficking. And it just kept going and going and going. So it's now been about a five-year partnership and lots of great work together. >> And catching bad guys. >> Yeah, I mean, their publicity of the National Human Trafficking Hotline has led to a major increase in calls. Airport signage, more employees looking for it, and I actually do believe that the notion of flying, if you're going to be a trafficker, flying on a Delta flight is now a much more harrowing experience because everyone's kind of trained, and eyes and ears are looking. So you're going to pivot towards another airline that hasn't done that training yet, which now speaks to the need that once one member of an industry steps up, all different members of the industry need to follow suit. So we're encouraging a lot of the other airlines to do similar training and we're seeing some others do that, which is great. >> Yeah, and how much of it was from the CEO, or did he kind of come on after the fact, or was there kind of a champion catalyst that was pushing this through the organization, or is that often the case, or what do you find in terms of adoption of a company to help you on your mission? >> That's a great question. I mean, the bigger picture here is trafficking is a $150 billion industry, right? A group of small nonprofits and cops are not going to solve it on their own. We need the big businesses to enter the fight, because the big businesses have the resources, they have the brand, they have the customer base, they have the scale to make it a fair fight, right? So in the past few years we're seeing big businesses really enter the fight against trafficking, whether or not that's big data companies like AWS, whether or not that's social media companies, Facebook, whether or not that's hotel companies, like Wyndham and Marriott, airlines like Delta. And that's great because now the big hitters are joining the trafficking fight, and it happens in different ways, sometimes it's CEO-led, I think in the case of Delta, Ed Bastian really does take this issue very seriously, he was hosting events on this at his home, he's hosted roundtables of other CEOs in the Atlanta area like UPS, and Chick-fil-A, and Home Depot, and Coca-Cola, all those Atlanta-based CEOs know each other well, he'll host roundtables about that, and I think it was kind of CEO-led. But in other corporations it's one die hard champion who might be like a mid-level employee, or a director, who just says, "We really got to do this," and then they drive more CEO attention. So we've seen it happen both ways, whether or not it's top-down, or kind of middle-driven-up. But the big picture is if we could get some of the biggest corporations in the world to take this issue seriously, to ask questions about who they contract with, to ask questions about what's in their supply chain, to educate their workforce, to talk about this in front of their millions of customers, it just puts the fight against trafficking on steroids than a group of nonprofits would be able to do alone. So I think we're in a whole different realm of the fight now that business is at the table. >> And is that pretty much your strategy in terms of where you get the leverage, do you think? Is to execute via a lot of these well-resourced companies that are at this intersection point, I think that's a really interesting way to address the problem. >> Yeah, well, it's back to the 25 types, right? So the strategies depend on type. Like, I don't think big businesses being at the table are necessarily going to solve magazine sales crews, right? They're not necessarily going to solve begging on the street. But they can solve late night janitors that sometimes are trafficked, where lots of big companies are contracting with late night janitorial crews, and they come at 2:00 a.m., and they buff the floors, and they kind of change out the trash, and no one's there in the office building to see those workers, right? And so asking different questions of who you procure contracts with, to say, "Hey, before we contract with you guys, "we're going to need to ask you a couple questions "about where these workers got here, "and what these workers thought they were coming to do, "and we need to ID these workers." The person holding the purse strings, who's buying that contract, has the power to demand the conditions of that contract. Especially in agriculture and large retail buyers. So I think that big corporations, it's definitely part of the strategy for certain types, it's not going to solve other types of trafficking. But let's say banks and financial institutions, if they start asking different questions of who's banking with them, just like they've done with terrorism financing they could wipe out trafficking financing, could actually play a gigantic role in changing the course of how that type of trafficking exists. >> So we could talk all day, I'm sure, but we don't have time, but I'm just curious, what should people do, A, if they just see something suspicious, you know, reach out to one of these kids selling magazines, or begging on the street, or looking suspicious at an airport, so, A, that's the question. And then two, if people want to get involved more generically, whether in their company, or personally, how do they get involved? >> Yeah, so there are thousands of nonprofit groups across the country, Polaris is in touch with 3,000 of them. We're one of thousands. I would say find an organization in your area that you care about and volunteer, get involved, donate, figure out what they need. Our website is polarisproject.org, we have a national Referral Directory of organizations across the country, and so that's one way. The other way is the National Human Trafficking Hotline, the number, 1-888-373-7888. The Hotline depends on either survivors calling in directly as a lifeline, or community members calling in who saw something suspicious. So we get lots of calls from people who were getting their nails done, and the woman was crying and talking about how she's not being paid, or people who are out to eat as a family and they see something in the restaurant, or people who are traveling and they see something that doesn't make, kind of, quite sense in a hotel or an airport. So we need an army of eyes and ears calling tips into the National Human Trafficking Hotline and identifying these cases, and we need survivors to know the number themselves too so that they can call in on their own behalf. We need to respond to the problem in the short-term, help get these people connected to help, and then we need to do the long-term solutions which involves data, and business, and changing business practice, and all of that. But I do think that if people want to kind of educate themselves, polarisproject.org, there are some kind of meta-organizations, there's a group called Freedom United that's kind of starting a grassroots movement against trafficking, freedomunited.org. So lots of great organizations to look into, and this is a bipartisan issue, this is an issue that most people care about, it's one of the top headlines in the newspapers every day these days. And it's something that I think people in this country naturally care about because it references kind of the history of chattel slavery, and some of those forms of slavery that morphed but never really went away, and we're still fighting that same fight today. >> In terms of, you know, we're here at AWS IMAGINE, and they're obviously putting a lot of resources behind this, Teresa Carlson and the team. How are you using them, have you always been on AWS? Has that platform enabled you to accomplish your mission better? >> Yeah, oh for sure, I mean, Polaris crunches over 60 terabytes of data per day, of just like the computing that we're doing, right? >> Jeff: And what types of data are you crunching? >> It's the data associated with Hotline calls, we collect up to 150 variables on each Hotline call. The Hotline calls come in, we have this data set of 50,000 cases of trafficking with very sensitive data, and the protections of that data, the cybersecurity associated with that data, the storage of that data. So since 2017, Polaris has been in existence since 2002, so we're in our 17th year now, but starting three years ago in 2017 we started really partnering with AWS, where we're migrating more of our data onto AWS, building some AI tools with AWS to help us process Hotline calls more efficiently. And then talking about potentially moving our, all of our data storage onto AWS so that we don't have our own server racks in our office, we still need to go through a number of steps to get there. But having AWS at the table, and then talking about the Impact Computing team and this, like, real big data crunching of like millions of trafficking cases globally, we haven't even started talking about that yet but I think that's like a next stage. So for now, it's getting our data stronger, more secure, building some of those AI bots to help us with our work, and then potentially considering us moving completely serverless, and all of those things are conversations we're having with AWS, and thrilled that AWS is making this an issue to the point that it was prioritized and featured at this conference, which was a big deal, to get in front of the whole audience and do a keynote, and we're very, very grateful for that. >> And you mentioned there's so many organizations involved, are you guys doing data aggregation, data consolidation, sharing, I mean there must be with so many organizations, that adds a lot of complexity, and a lot of data silos, to steal classic kind of IT terms. Are you working towards some kind of unification around that, or how does that look in the future? >> We would love to get to the point where different organizations are sharing their data set. We'd love to get to the point where different organizations are using, like, a shared case management tool, and collecting the same data so it's apples to apples. There are different organizations, like, Thorn is doing some amazing big data-- >> Jeff: Right, we've had Thorn on a couple of times. >> How do we merge Polaris's data set with Thorn's data set? We're not doing that yet, right? I think we're only doing baby steps. But I think the AWS platform could enable potentially a merger of Thorn's data with Polaris's data in some sort of data lake, right? So that's a great idea, we would love to get to that. I think the field isn't there yet. The field has kind of been, like, tech-starved for a number of years, but in the past five years has made a lot of progress. The field is mostly kind of small shelters and groups responding to survivors, and so this notion of like infusing the trafficking field with data is somewhat of a new concept, but it's enabling us to think much bigger about what's possible. >> Well Brad, again, we could go on all day, you know, really thankful for what you're doing for a whole lot of people that we don't see, or maybe we see and we're not noticing, so thank you for that, and uh. >> Absolutely. >> Look forward to catching up when you move the ball a little bit further down the field. >> Yeah, thank you for having me on. It's a pleasure to be here. >> All right, my pleasure. He's Brad, I'm Jeff, you're watching theCUBE. We're at AWS IMAGINE Nonprofits, thanks for watching, we'll see you next time. (futuristic music)

Published Date : Aug 13 2019

SUMMARY :

Brought to you by Amazon Web Services. and one of the biggest issues is human trafficking. for people that aren't familiar with the company. and it's part responding to day-to-day cases Is that just domestically here in the States, And the third bucket is anyone forced to work it's the child sex trafficking you can kind of understand so the first thing that we do that we're kind of known for and the other tools that we have today, for each of the 25 types. Absolutely, and you know, you think first they're hustlin' Where the crew says, "If you act up "because I kind of didn't obey one of the rules." most of the people that are going to be watching this interview So the first big report that we released and lots of great work together. all different members of the industry need to follow suit. We need the big businesses to enter the fight, in terms of where you get the leverage, do you think? So the strategies depend on type. or begging on the street, and the woman was crying Teresa Carlson and the team. and the protections of that data, and a lot of data silos, to steal classic kind of IT terms. and collecting the same data so it's apples to apples. and groups responding to survivors, Well Brad, again, we could go on all day, you know, when you move the ball a little bit further down the field. It's a pleasure to be here. thanks for watching, we'll see you next time.

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Devnet Create Analysis | Devnet Create 2019


 

>> Live from Mountain View, California. It's The Cube. Covering, DevNet Create 2019. Brought to you by Cisco. >> Hi welcome to The Cube. Lisa Martin with John Furrier. We are live, at Cisco DevNet Create 2019 in Mountain View at Computer History Museum. John this is the third DevNet Create, but DevNet started as this ground, small sort of grass roots out of Cisco Live, about five years ago now. You and I just came from the keynote, which I think is really awesome to highlight that it was kicked off by two, strong female leaders in technology, who will be on our program this week. I'd love to get your perspectives on what you saw and heard today, knowing the history of DevNet as you do. >> Yeah you mentioned strong leaders, Susie Wee has been promoted to Senior Vice President and CTO of DevNet and DevNet Create. Two communities and that's been a really an interesting ride because she's gotten real technical jobs but adds a good business acumen and saw the wave early on. I remember I met Susie Wee at I'd say almost seven years ago, in and around Palo Alto. She always had that energy, but she's super technical, great business mind. She saw the open source wave and cloud connecting. And then when she came to Cisco with DevNet, she took that open source kind of mojo, and took the developer communities, which were very centric, Cisco, plumbing, moving packets from point a to point b, configuring large scale networks to much more of a developer focus. And she's evolved that program and started DevNet create three years ago to bring in the cloud native, used to be called the hoodie crowd, you know the people who are coding in the cloud. Cloud first, and she she wanted to cross pollinate them together with DevNet. And the result of that experiment or that that kind of mechanism and community collaboration has changed the face of CisCo. >> Absolutely. >> You can see Chuck Robbins as the Ceo and others within Cisco, seeing that they're on this new wave and it's actually paying off dividens for them, it's changed their strategy, customers like it, the community has grown, the metrics are all kind of up in to the right, on terms of adoption. So, success from that experiment, their doubling down and their bringing real technology, real workshops, a real co-creation, a real community vibe and it's working. So again don't fix what's not broken. >> In terms of their community, one of the things that Susie mentioned this morning is that the DevNet community's now over 585 000 members strong. They talk about this, yes it's a conference but it's also, it's a strong community, it's hands on learning. It's code and the theme of the event: See it. Learn it. Code it. They did a great job only in the first hour of the keynote about actually showing some great examples and also how to your point, Cisco is evolving. Digitally, IT transformation and how they are really staying quite far ahead of their competition. >> It's interesting because you know, one of the things that we've been doing in theCUBE for 10 years, we seen a lot of trends come and go. This one we like a lot. We use the term builders creators, Andy Jassy used that term builders. That's what they talk about this new era of this renaissance of value creators. They're building stuff and with now Cloud Computing and with now AI and other things coming to the table, there's an unlimited tool set out there and platforms with and computing cloud cloud computing, you can now build things faster. So conceiving it, understanding and building it is critical. Now what's interesting about DevNet Create is that they're bringing in that again, that community vibe where, it's not just a bunch of hackathons and a bunch of rah rah, use our code and get developers locked into a platform. It's authentically and genuinely ripe, meaningful to the developers because they do it in a group setting. They do it with community. So the have, they do have hackathons, they've got creation tools, they've got different stations and they roll out the toys if you will. Meraki has things going on here, there's all this new technology. So Cisco's bringing the goods to the party. It's like I always say, when someone brings beer to the party, you know and we're going to have some good times. So they're bringing the technology and the tools in to the community without kind of jamming it down their throat. That creates a good vibe. That's cross-pollinating to the core Cisco with DevNet, and every year that DevNet's section within Cisco Live becomes the number one place everyone goes to because that's where the feedback is and the company's listening. And this is part of their fly wheel. So this is a game changer for Cisco because their culture was pretty much build networks, run them, lock'em down, highly secure. Everything's good but now the world's changed. They want programmability and this again, changes the culture of Cisco. So I think it's a great move and I love this, I love the vibe here and this event's popular because, there's engineers here. So you have people who are savvy with code, savvy with community and savvy with building and creating and being creators. So design thinking to hackathons to any workshop you can imagine. >> And there's engineers here to your point of all, and Susie's point to have all levels of all ages. And I'm always curious about the engineers and the folks who've been in an institution for a very long time and are very use to working in that traditional model. How do they get access to the right education tools, to start shifting their own mindset, because really, in this day and age, they don't have a choice. Whether they want to continue working at a company like a Cisco or any other company these days that has to be a tech company. So you see all levels of coding experience here. They provide education for that. You also see all levels of of the veterans, those in their early stages of their career. Those in their mid-careers. So a lot of collaboration in this community. >> And the CEO Chuck Robbins points out and always kind of gives Susie Wee call outs, because even though developer.cisco.com is the destination that you can go to learn. Go to developer.cisco.com to get kind of the goods. That's from Cisco's perspective. But what Susie and Chuck have recognized is that, the real action is out in the organic community. So the co-creation, the learnings. This is where the canary and the coal mines are. This is where, companies are getting early feedback on products. This is where peers are starting to figure out what's right. So if companies listen to their community, not just provide the goods and have, some destination urls to go to, to get onboarded. The action is in the organic communities. That's where people are developing friendships. That's where discovery's happening. People are learning and that's where the action's at. So Cisco's actually listening. So this is an interesting change for Cisco. >> And it seems like, to your point on the listening, it's almost becoming the lifeblood of Cisco and really giving them this fuel and momentum >> Yeah >> To allow any type of industry. The SVP and CT, I think CTO of Meraki was saying, we don't build specific solutions for specific verticals. This is for all types of verticals, because every industry has to transform and become a tech company. But this community really seems like it's, I don't want to say a rebirth of Cisco but it almost feels somewhat something similar, but really that lifeblood of this transforming organization. >> Well one of the things that's not going to be on, on the financial analysis in the, when you look at the 10 k's and all the Wall Street guys are going to go sprint got the numbers and look at the, the financial analysis. Try to figure out where the stock's going to be. But if you at what's going on with Cisco. If they can continue to do what they're doing. If they convert their core developers in DevNet and allow this cross-pollination and with cloud computing. You're going to start to see product transformations happen faster. You're going to start to see business results that aren't reflected at any kind of performer or forecasted financial analysis. And this is going to put pressure on Cisco. Cisco is under a lot of pressure and this old school guard managers at Cisco, are like 'no the data center, we got to hold down' and so, if you don't, if Cisco doesn't cannabilize itself by bringing in the new, faster. That's the trick of the management. This is Chuck Robbin's hardest job as the CEO. It's to understand when to start cannabilizing pre-existing businesses like data center servers, UCS and have them change over to a scalable revenue model on the cloud side. So they're in a transition. I think they're in good shape. The wave they're on is positive, but the real upside to this is, if they can convert those network engineers into coders. They would have an army of awesome, talented people setting and building out the next generation data centers to cloud computing architecture and serp. Strategic strike if they can pull it off and they continue to do it. That's what we're going to be watching. >> Well we're about six weeks or so I think, before Cisco Live, which is down in San Diego. The Cube will be there. >> Yeah. >> What are you thinking, you gave a pretty good, kind of your perspectives and what you're thinking. What are some of things that you think we're going to hear and see and feel and learn from Cisco Live ? >> I think we'll hear some more of the same of what we're seeing and hearing when we start Cisco Live. I still think that Cisco's got some internal re-organizations to do to get on this wave. There's an article in Fortune magazine this week, talking about the rise and fall of Kleiner Perkins. And the thesis was there on the wrong way, missed two generations of investments. Cisco right now has to decide what wave they're going to be riding in to the future. That's Chuck Robbins' strategic imperative, and I think we're going to start to see more and more of the Cisco ship turning to get on the wave of cloud, cloud native, hybrid cloud and I think multi-cloud is probably the biggest opportunity that Cisco has and I think in bringing multi-cloud as a multiple network, multiple programmable network. That to me is a wave worth riding. The question is, when doe he time the revenue? When doe the whole ship just go full steam ahead? I think it's still going to be in transition, but we'll probably hear more, more DevNet. More DevNet Create, more programmable networks, more use of data. A lot of multi-cloud. >> Yeah and there's, this year there are three tech tracks. One on Enterprise Transformation which is, something that we'll talk about with our guests over the next two days. And then we've got, businesses have real-time data access. AI, machine learning, infrastructures that are programmable. Now how are, what are the tools and the trends, that enterprises are using to generate business insights that actually drive outcomes. >> Yeah so I think that all these tracks kind of point to big high level pillar trends that I think Cisco has to really nail and I think, they have clear sight for this. They just got to put the wheels on the bus and get the bus rolling. And that is three areas. Application modernization. So renaissance and application development. So you're seeing a new kind of app developer emerging. We hear about that all the time. You know these guys want infrastructure's code. Those app developers are going to be coming in to the enterprise in a large scale, and they can either be hybrid and multi-cloud orient. So application modernization. A renaissance in applications. Cisco has to be on that and they got AppDynamics for that and a variety of other cool things. Hybrid and multi-cloud, absolutely is going to be the architecture for enterprises and third area is security. Those are the things I think, if Cisco could nail those three things. They would be well positioned. And they got to bring the tech to the table and their product leadership. So that to me I think that's, I think we're going to see a lot of that at Cisco Live and that's I think the core plan. >> Well we'll be listening for that over the course of the next two days. John and I are fortunate to be here for today and tomorrow with a spectrum of guests, from Cisco folks, DevNet folks, partners, users of the technology and members of, active members of the DevNet community. So John looking forward to being here the next two days. >> It's been great. >> Sick around >> John and I are going to be right back from Cisco DevNet Create 2019 with our first guest. (soft upbeat music)

Published Date : Apr 25 2019

SUMMARY :

Brought to you by Cisco. You and I just came from the keynote, and saw the wave early on. and it's actually paying off dividens for them, one of the things that Susie mentioned this morning So Cisco's bringing the goods to the party. and Susie's point to have all levels is the destination that you can go to learn. The SVP and CT, and they continue to do it. The Cube will be there. and see and feel and learn and I think we're going to start to see more and more Yeah and there's, and get the bus rolling. John and I are fortunate to be here John and I are going to be right back from

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Caroline Simard, Ph.D & Shannon Gilmartin, Ph.D | Women Transforming Technology 2019


 

>> From Palo Alto, California, it's theCUBE. Covering VMware Women Transforming Technology 2019. Brought to you by VMware. >> Hi, Lisa Martin on the ground with theCUBE at the fourth annual Women Transforming Technology event VMware, WT squared, one of my favorite events and I'm joined by two PhDs, both from, I'm going to say this one time, the Stanford VMware Women's Leadership Innovation Lab, we've got Shannon Gilmartin, senior research scholar. Hi, Shannon. >> Hi, great to be here. >> And we've got, great to have you, we've got Caroline Simard, managing director of the lab. Ladies, thank you so much for joining. >> Thank you, it's a pleasure to be here. >> So this event, we were talking about before we started, that you, walk into the keynote, opening keynote which in and of itself was electric but the energy that comes into the room with, VMware was telling me a little while ago, about 1500 live attendees. >> Incredible. >> Not even including those that were watching the livestream. The energy comes into the room and then, of course, this morning with Joy, I'm going to try to say her name, Buolamwini. The poet of code, the MIT researcher who started really, sharing with us the significant biases in AI. The energy, if it could even be down that more, I can't even imagine it, so. I can imagine the panel that you guys were on this morning was quite charged. The panel title was, I found interesting, Inclusive Innovators Designing For Change. So Caroline, talk to us about designing for change. You look through a design lens, what does that mean? >> Yeah, so I think what, to frame the morning, and then Shannon was the moderator, so I want, she picked the topic of design. But I think what Joy really showed is the power that is possible to realize when women and women of color and people from different dimensions of identity are included in creating technology and how much better technology will be for society, right? If all voices are included, and I would also say that some of her comments also make it clear that it is fundamentally irresponsible not to have diversity at the table in designing the technology of tomorrow. The consequences on different kinds of people and different populations are significant. And so this is why Shannon really picked this idea of, as engineers and designers and creators of this technology, how do you keep in mind the responsibility that you have? >> So yeah, talk to us more about the design and why that is so critical. >> And the way we positioned it for our panelists, it was titled Inclusive Innovators Designing For Change, and we were going to explore how meaningful change towards greater diversity and equity is realized in engineering cultures. And in the very technology that's being created. More specifically though, how do individuals and communities of people design for change in their technical environments? Even when this environment may not be initially very receptive to new ways of interacting. To new ways of thinking, to new ways of achieving. And so the whole panel was premised on this idea of people are designers of change in their environments. How does that happen? How do people interface with barriers to those design processes? And what is advice for the younger generation as they look ahead to their pathways as designers for change? >> Yeah, 'cause change in any context of life is hard. >> Yep. >> Yes. >> Right, it's an uphill battle. But designing for that change, I'm curious what some of the commentary was from the panelists about, when you're encountering, whether it's a company or a leadership group within a company that, to your point, isn't receptive, what were some of the comments or stories of how that was changed over time to become receptive and understand, the massive potential that that change can have? I mean we look at numbers like, companies with women on the leadership communities are far more profitable, so what were some of those, from, I don't get it, to, oh my gosh, why aren't we doing sooner? >> And we have this amazing range of perspectives represented on the panel, so we had a VMware CTO, chief technology officer Ray O'Farrell. And he was really talking about from a leader perspective, a key idea here when there are barriers and blocks and inertia, is to open things up and really start listening. And this is a skill and a talent and a group practice that is so little done, so infrequently done. So poorly done, sometimes. But really key in the face of those barriers is to actually say, instead of shutting down, open up and start listening to what's happening. Another one of our panelists, Susan Fowler who is the Time Magazine Person of the Year as one of the silence breakers in 2017, she was really talking about how, expect the steps, you're going to need to go through a lot of steps to make your voice heard. And ultimately, for Susan, she made the decision to go public with what she had encountered and was facing and grappling with and struggling, as were many of her colleagues. But she was really talking about the step by step process that's involved in a large organization, when you're hitting blocks, you just got to keep on fighting that good fight, and you also need to be doing your very best work at the same time, it's a high pressure situation. >> Yeah, absolutely. >> So. >> Absolutely, we also heard from Lisa Gelobter who is the CEO of tEQuitable, an organization that's creating a safe place for change agents to share their stories when they're encountering these blocks and this kind of unfair treatment. And she talked about, also, the need to do your best work but also the critical importance of community in being more resilient as you're trying drive change in your environment, right? And this is the kind of community that is being built today with this event, right? It's really paying attention especially for her, as a black woman engineer, being the only one constantly at the table fighting for change has been something that she has realized she needs to pay a lot of attention to so that she can be much more resilient as a leader for longterm change. Another topic that I think, in terms of generating change, that really came through both in the panel and during this morning's keynote, and that we pay a lot of attention to at the lab, is to really highlight bias. Is to really diagnose what is really happening in organizations? Or in AI, as we heard from Joy this morning. So a lot of people genuinely aspire to treat others fairly, right? But they don't realize that their workplaces are so far from being a meritocracy, that there's these structural inequalities that are really embedded in all of the ways that people are working. And so when you're able to show people exactly how it shows up in their company, right? The promotion rates for women of color for example, being lower than for other people, the exact points of data that they need to see, that they're not treating people the same way and creating the same kind of pathways for impact for different kinds of people, then that has a lot of power to drive change because a lot of people, then, will be very motivated to say, okay, I see this is happening in my org every day. Now I can design a different approach, right? How do I redesign the way I'm working today? In my units. >> And take action. >> And take action. >> 'Cause you actually have the data, it's such a dichotomy at times, that we have, we're surrounded by data especially in Silicon Valley. But one of the things that shocked me, what Joy showed this morning is, when she put on blast, IBM, Microsoft, and what was it, Face++, about looking at all of the built in biases to facial recognition. But, one of the things that really also, I thought, was interesting, was that, she went and showed this to these companies, who responded, and those numbers are actually improving. And then when she said, hey Amazon, so, the fact that even that one person is able to show, look at some of the massive problems that you're training these models to have, they need to be able to see that. So the highlight, I think, the highlight the bias, and the communicate, communicate, communicate and listen, are three critical elements to any place being successful. >> Exactly. >> Exactly. One additional part of both Joy's presentation and Lisa's comments too, really spoke to action needing to take an intersectional approach. So Joy's data breaks it down by race and gender and all of a sudden, you see completely different trends. Lisa spoke to that as well in her comments. Key to this designing for change process is really wearing the hat of someone who is looking through the world with an intersectional lens. And understanding how different axes operate together uniquely for different groups. And that's when you see these biases being highlighted really in full force, in full relief. So both of these points and these presentations really brought that up. >> Yeah and the intersectionality that Joy talked about was even evident and you could parallel it to, why it was important to look at all these different sources of facial recognition data, how disparate some of them were. >> Right, right. >> I know. >> Without that lens you couldn't see all of that variation even across the different providers. >> Exactly. >> Yeah, and she talked, too, about how everything is classified in a binary way, right? In terms of gender identity, and then where data doesn't even see people who are Non-Binary. >> Exactly. >> So it's like, >> That's still a huge omission >> again, exactly. That we have a lot more work to do to have data that truly captures all the dimensions we're interested in. >> It does, it does. Long way to go, but the fact that it's being highlighted and opportunities like, not just what VMware does but the lab as well. So let's talk a little bit about the lab. It kind of got its start in 2013 when then Stanford president Doctor John Hennessy, provided some funding. I had the opportunity to interview him last week, lovely man. Last year VMware did a big endowment of about 15 million. What's going on, Caroline, we'll start with you, what's going on at the lab? What are you guys studying now? What are some of the breakthroughs that have been uncovered in the last 12 months? >> Yeah, so a big part of our lab's work and since we began this work, has been to really bridge the gap between research and practice, right? And so a lot of why there's little progress being made is because you have a lot of research happening in the academy, in the ivory tower, if you will. And then you have a lot of innovative practices being tested but without necessarily the research foundation and the research frameworks to truly evaluate it. And so, our work has been to really bridge those two things together. And explore those boundaries so we can have more innovative research but also more evidence based practices come in, right? And since the VMware endowment we've been able to, really grow in our aspirations in the kind of data, in the kind of research questions that we can really ask. One of them is this focus on the more intersectional, longterm study of really documenting the experience of women of color. And really understanding the nature of their career pathways across racial dimensions, right? And really highlighting a lot more of, qualitative deep insight, generate their stories, right? And really centering their experience. The other one is, investing in large scale datasets that capture gender, race, age, and other identity dimensions and look at their longterm career trajectories. This is actually work that Shannon is leading. So we have an exciting dataset where we have people through five years and we see what happens to them, who gets promoted? Who doesn't? Who gets top talent designation, who gets a salary increase? Who, and then we're excitingly, looking at social network data, so who's meeting with who? And then what kind of connections do you need to be able to advance in your career? And are there some systematic inequalities there, right? And a big part of our work then is to design these interventions where we work with companies to test what we call a small wins approach. It always starts with diagnosis, here's what's going on in your very specific workplace and your culture. And then we co-design with leaders and managers. It doesn't work for us or HR or anybody to say, go do this, or you should do this. It's really about really engaging managers who want to do better in coming up with the design fix, if you will, that they can come up with. Informed by our research, so it's a co-design process. And then we roll it out and we test the outcomes pre and post, so. We're doing a lot more work now to disseminate what we're learning through these interventions so that other organizations can implement this very similar approach. >> First I love that it's called an intervention. 'Cause I think that's incredibly appropriate. (Shannon and Caroline laughing) Second, are you seeing an uptick in the last year of companies, obviously VMware and Dell being two great companies that are very focused on, not just women in technology, but I loved how Joy said today, it's women and people of color are the underrepresented majority. Are you seeing an uptick in companies willing to, accept the intervention and collaborate with you to really design from within for that change? >> Yes absolutely. And I would say that in this industry people are comfortable with piloting things and doing a little R and D experiment, right? So it's also a culturally appropriate way of thinking, okay, what if we try this, and see what happens? And so I see a lot of energy from organizations and based on what you were talking about, it's also, I think companies are aware that it's, the overlapping dimensions of identity increasingly aware, are within their own walls, but then, in their consumer base, right? So how is their product affecting different kinds of people? Are their customers experiencing bias from the very platforms that they build? And so I think that's also a very powerful, entryway into this intersectional conversation because, the product is, so foundational to the business of the company. >> It is, and especially event after event that we cover on theCUBE, customer experience in any industry, is critical because as consumers of whatever it is, we have so much choice. Shannon last question for you. One of the things that always interests me is the attrition rate being so high in technology. I'm curious what you guys are finding in the lab with, mentioning following women on maybe their first five years. Are you seeing any glaringly obvious, challenges that are driving that attrition? Is it, it's got to be more than the motherhood penalty. >> Right, right. We're looking at a range of, what we call pathway outcomes really for young people just starting out in their very first, second jobs, where they are several years later, we're looking at odds of promotion, odds of leaving the company, odds of moving and making a lateral move into some other kind of line of business, maybe taking them out of, let's say, a technical role and moving them into a non technical role. Each and every one of those critical moments is worthy of deeper study for us. And what we're doing, really, is taking this intersectional lens and understanding how do those different moments vary for different groups of women? It's not enough just to say, all women have some x percentage of an attrition rate. We're trying to understand how attrition really varies by sub-groups of women. And how that varies over time with what interactions that precede it and then follow. One of the themes that we've really been looking at in, for instance, attrition stories, is the assignment. Which projects, what kinds of assignments are people getting in their first few years on the job? How are some of those make or break? With what net consequence for women, men, from different racial ethnic backgrounds, different ages, different countries? And understanding, really, the role of those assignments in someone's longer term career pathway, just how important they are. And what kinds of interventions we can hand design to really elevate access to the best assignments for everyone, basically. >> Gosh, you guys, this is so fascinating and so inspiring what you're doing at the lab I wish we had more time, but you'll have to come back next year! >> Exactly. >> Absolutely we will thank you so much for having us. >> Thank you so much, Lisa. >> Thank you. >> Thank you. >> Thank you so much. For theCUBE I'm Lisa Martin, on the ground at WT squared, thanks for watching. (electronic music)

Published Date : Apr 23 2019

SUMMARY :

Brought to you by VMware. Hi, Lisa Martin on the ground with theCUBE managing director of the lab. but the energy that comes into the room I can imagine the panel that you guys were on is the power that is possible to realize and why that is so critical. And the way we positioned it for our panelists, from the panelists about, when you're encountering, and blocks and inertia, is to open things up And she talked about, also, the need to do your best work all of the built in biases to facial recognition. and all of a sudden, you see completely different trends. Yeah and the intersectionality even across the different providers. and then where data doesn't even see all the dimensions we're interested in. What are some of the breakthroughs and the research frameworks to truly evaluate it. accept the intervention and collaborate with you and based on what you were talking about, One of the things that always interests me One of the themes that we've really been looking at Absolutely we will thank you Thank you so much.

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Zac Mutrux, Insperity | ACG SV Grow! Awards 2019


 

>> (Announcer) From Mountain View, California it's the Cube. Covering the 15th Annual Grow! Awards. Brought to you by ACG SV. >> I'm Lisa Martin with the Cube, on the ground at the Computer History Museum in Mountain View, California for the 15th Annual Grow! Awards for the Association of Corporate Growth Silicon Valley, ACG SV. That's a mouthful. I'm here with one of the ACG SV board members, Zac Mutrux, the District Sales Manager at Insperity. Hey, Zack, it's great to have you on the Cube. >> Thank you so much, Lisa, I'm pleased to be here. >> So before we talk about what you're doing here at the 15th Annual Grow! Awards, tell our audience about Insperity. I was reading, I love taglines. >> Yes. >> And I see on your homepage, Insperity is obsessed with delivery HR mastery. Wow. >> Oh yeah. >> Obsessed and mastery. Those two words just jumped out. Tell us a little bit about what you guys do. >> Impressive, isn't it? Well, we actually just adjusted our tagline to HR that makes a difference. And that's really what it's all about. We feel like companies that are growing, if they're going to make it from good to the best, it has everything to do with the people. Attracting the best people and keeping them, developing them over time, and that's exactly what we do with our clients. >> So Insperity has been in business since 1986, and if I think of today's modern workforce, highly mobile, distributed, there's the whole on-demand industry. You guys have seen a tremendous amount of change that now can be massively influenced, and your customers can, using technology. Give me a little bit of that historical perspective on Insperity's inception and today's workforce, and how you're helping them attract and retain the best talent. >> Oh, absolutely. Well, when the company started it was in a maybe a 200 square foot room with one telephone between the two co-founders. There's no such thing as email. So, absolutely, there's been immense technological changes and there continues to be. I think that's one of the things that has been responsible for Insperity's success is its adoption of technology. Today we are as much a technology company as we are an employee benefits company, or an HR consulting company. It's really about creating a positive experience for the employees. That's part of being a competitive employer. >> Well it has to be a positive experience, right? For your customers. Because acquiring great talent is one thing, retaining them is another. And I want to kind of pivot off the retention there for a second. As the District Sales Manager, I was asking you before we went live, tell me maybe one of your favorite stories, and you said, "Wow". One of the great things, you guys are coming off great growth and FY18 revenue growth. One of the great things that Insperity has been really successful at is customer retention. And that's hard. You're proud of this. Tell us about that statistic that you mentioned, and how it is that Insperity is evolving and innovating over the last few decades to keep that retention number as phenomenal as it is. >> Well, Insperity's been named one of the most admired corporations in the country, actually, five years in a row by Fortune magazine. And that's the kind of press that you can't buy. One of the accolades that I'm most proud of is that in the past year our own employees named us one of the top 100 companies to work for in the United States. Which is, I think, the proof that we really know what we're doing with our clients. Because there are a lot of different companies out there, various competitors, and almost none of them are on that list. So, it's living our values and expressing through our service team, our extraordinary service team, that, I think, keeps our clients coming back to us year after year. About 85% renew. That's been consistent. A high level of client retention for the past three years. Even more extraordinary is that we've been growing both top line and bottom line revenue at the same time. So there's just a testament to our leadership, to our co-founder and CEO, Paul Sarvadi, and to the best of team-- >> But it sounds like it's a lot of symbiotic relationships between the internal retention at Insperity that is maybe leading through to your customers seeing, hey, there's not a high turnover here. These people are doing, they love what they're doing. They're working for a good company. So there's probably a lot of symbiotic behaviors. >> Well, that's exactly right. I think you really hit the nail of the head. It's about culture. It's a culture that starts from the top with leadership, and it filters down throughout the organization. And we're not looking to do business with every single company. We're looking to do business with the companies that believe the things that we believe. That is, companies that have high levels of commitment, trust, communication. They do better financially then companies that don't have those things. >> And along those lines, mentioning just before we wrap here, we are at the 15th Annual ACG SV Awards tonight, where they're honoring two award winners. The Outstanding Growth Award winner is Arista Networks. And the Emerging Growth winner is Adesto Technologies. I'm excited to talk to them later. But I wanted to get a little bit of perspective on you've been involved as a board member of ACSG since last year. Tell me a little bit about what makes ACG SV worthy of your time. >> Oh, absolutely. That's a great question. It's just an extraordinary community, I think, of the top leaders in Silicon Valley come together. The monthly Key Notes add a lot of value. It's an intimate setting and there's real conversations that are taking place on topics that are relevant to today's professionals. So for me to be able to engage and hopefully add some value as a board member is privilege. >> And you can hear probably a lot of those conversations going on right behind Zac and me tonight. Zac, it's been a pleasure to have you on the Cube. Thank you so much for giving us some of your time. >> Oh, right, thank you, Lisa. >> For the Cube, I'm Lisa Martin on the ground. Thanks for watching. (pop electronic music)

Published Date : Apr 18 2019

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Glen Hartman, Accenture Interactive | Adobe Summit 2019


 

>> Live from Las Vegas. It's the Cube covering Adobe Summit twenty nineteen brought to you by extension for interactive. >> Hey, welcome back it when Cube live coverage here in Las Vegas are doubly. Summit twenty nineteen. I'm John Murray with Jeffrey, my coz this week. Two days of wall to wall coverage. Our next guest is Glenn Hartman. North America lied for a censure Interactive. Thanks for joining us. Hey, thanks for having me. Great beer. So you guys are doing some great stuff around the creativity, peace, doing great customer experience. Implement taste. We have a great walk through from a lot of the folks from your organization. You're designing up ideas and products, delivering them and then operating them. Nice model. Yeah, thanks. Is that your business model that has network, What century? Interactives business model. I mean center and >> really about one thing. It's about creating, delivering and running the best experiences on the planet. We help our clients do that for their own customers. And when >> we talk about experience, a lot of people have different definitions for that, especially at the conference here. It's not necessarily an experience of a website or a mobile app or u X is people use it. It's really anyway, a brand engages with a customer. It's not just marketing. Either it could be sales or customer service loyalty. Anything anyway. A brand promise can be delivered. Teo to customers. One of things that I've noticed with you guys is that it's a talk track and thought leaders around a new creative and new creativity. And Toby honestly with software that they haven't now the cloud you're seeing in the marketplace. We saw this at Sundance two years ago. A new kind of creative is, um, organically coming into the marketplace with more channels to direct to consumer, whether it be to be or be to see you and now have new kinds of mechanisms to take product, whether it's APS or content or movies, You start to see this democratization really starting to happen. How is that changing? How you guys helped us is because now they now have new capability. They can tell their story in a different way. They have access to new kinds of channels that weren't there before. How is that changing the business, in your opinion, die in a profound way? So I mean, everybody knows that marking is inextricably linked >> to technology and data. Everybody knows that. But when >> we are thinking about the new, creative and own ways that you can tell stories and create experiences. We look at experience very differently. I mentioned before that it was all about all the different touch points in the ways people interact with the brand. But when we look at experience, we call it the Big E. And the biggie actually stands for empathy. And it's understanding how to define what a brand experience means to that customer and defining success in terms of that customer. And you know, Jeff and John, you guys air not to find by your data set or what you bought last week. You could be very different types of people in different situations and understanding ways to empathize with you in the moment and having experiences change in the moment and having creative play, a part of that and data play. A part of that is the big hot. It's a new way of looking at things, and the last part of that, too. And the big is about emotion. So when you have a big brand that has some emotional connection, you know you love this brand for an automotive or you love this hotel chain or there's some brand a connection you have. How do you have that connection flow through every touch? Point and data and technology can enable that. But it's really empathy and emotion. That's the driver. How do you get empathy and creativity to work together? Because you now have an accelerant with data you mentioned getting to know people's empathizing with them in the moment it's contextual. I could be having a great day or a bad day or driving my kids to school of whatever's going on with me. It certainly there might be some data out. How do you get the creativity and the empathy to work together in your mind? You see that appointment? That's the nice parties. More than ever, we have different data sets that can help us do that. Just give you a couple of examples. Um, instead of understanding how to market >> to someone so they'LL buy the next product on basing. That may be on their demographic, maybe basing it on their preferences. You've hear all these terms and marketing for years, and you can understand what they bought. >> Instead of understanding that, why don't we try and look and use data which you could easily do today to understand why they bought something so it could be something as simple as like a I don't know, Cpg example. Maybe have shampoo and you could say, Well, they bought these kinds of things before, So maybe they'LL buy that champion. But if they know that, you know, maybe Jeff is equal friendly are John. Maybe you're more into things that maybe you buy that shampoo because you care about animals and they know they don't test them on animals. Or maybe it's something more about experience that that particular shampoo won't make your daughter cry when you ship your her hair. And it helps that experience that that's the reason why it actually helps me. You're empathizing in the moment with something that is meaningful that you care >> about. It's not about a better deal or >> better price or some kind of feature. It's something actually about you more meaningful, much very meaningful interaction. Data set is that because there's no data before, is it more? There's more signals, potentially to get exposed to that, because that's a hard data points to get. I mean, to find the why is a holistic kind of perspective. It's true, but I mean, I think it's more of a mind set. The date is there, but the mind set has been different. Over time, people were looking to technology every buzz word in the world use big data and personalization. Aye, aye. And then now it's a I and machine learning and like, Well, that's great. And they're all wonderful enablers, as I said, but it has to be driven by empathy first. So it all starts. >> I mean, we've been saying this forever customer, centrist city and a customer >> concerts. But really, I mean, for real. If you start to use those data sets, aunt have the mindset has to be a c M. O. R. A brand manager is someone who actually it's advocating for the customer, and they're willing to say, No, I don't need big data. I don't need all the data. I need this gold nugget part so I can speak to John. >> It's interesting plate, as you say, the emotional part of the biggie. Also, I think it is the old Coke commercial, right raw one world together, and we all cry and there's some great McDonald's commercials, right when you talk about you think beyond that to the to the empathy. I can't help but think of kind of the whole purpose. Purpose driven, mission driven companies. You know, kids coming out of college want to work for mission driven, cos we heard it over and over. And the key notes, you know, we're not a product company, not even really a service company. But we're committed to two, an ideal to the mission. Beep. Be partners with us, be our customer. Let's have a relationship that goes so much deeper and longer than any particular transaction is that kind of that tied it, that that is a part of it? >> Absolutely. Now, the interesting thing of what you said is that people are >> tied to a purpose and maybe something that's meaningful in a broad sense, absolutely. And that's a wonderful place to start. And you can start to align products and services in that way, >> the way he talked about, like, shampoo and, you know, animal testing, right? Well, >> it's a good one, but the next one is really getting a little bit Mohr down to you. So I think all that is great, but really understand what you need in the moment, because what happens is it. Some of those things may change if you are shopping at a grocery store every >> Saturday for your family and you're used to doing down your attitude. There might be different then when >> you're shopping, when your kid is sick and you got pulled out of work and you got to get there to get the prescription, you're into speed and your stress in the moment they're versus. Maybe >> on Saturday you're like all try some new coupons and try some new things and go by. The little tasting >> station is actually behaviors that you want to understand in the moment. That is a big part of that as well. But the key thing to hear is, let's think of this when you deal with empathy. It's not just getting to know all those things. Even if it gets to that level, it's actually changing the way marketers think about talking to communicating and relating to customers even the language that they use. I mean, think of it >> today. I mean, >> still, people use marketers are their marketing to people. It's, uh, that's acquire customers. Let's convert wind developers over good. We don't win their helpers over. And what was the last time you guys were real excited about getting converted? Okay, it's not a fun experience, right? So if you even changed, I might send you say, Let's market with someone or let's let's help them. You actually create experiences that are useful and helpful not about conversion and not a business metric. But success is defined by the customer. How are you guys playing this? Because this is really kind of ties on multiple threads. I mean, the whole nother community angle to people belong to communities in context to their life. And they engage. And when they engage his emotional connection to a group of this and some cohorts is the worker. Thank you. Okay, groups. But they're friends and colleagues, or whatever could be you guys were. The point is, with customers, take us through a use case day in the life of empathy, deployed into how you guys do business with the big Branson and one of the success. How do you make it happen? What's the engagement look like? How does someone do this? So they just wake up one morning, say Okay, I'm gonna have more empathy. They also call you guys up. What happens? Like what? Take us through What? Certain evidence was made in the slide. I could give you >> a little bit of it. An example of how stars we've been talking a little bit more dramatically about sick kids and testing on pets and animals and things like that. Not testing the pets. Can you imagine? I'd really be >> horrible. But single graphic of the users individual personal things is hard, right? So? Well, I mean, the whole point of this is that when you really get into the mechanics of how this works, I'll give you an >> example. It's a little bit less dramatic. OK, so it's a telecommunications company. Telco company. That's selling. You guys know what? Triple play? Yeah. Okay, So you have It's >> a cable and a phone, right? All it's it's like a commodity product writers. There's no emotional thing necessarily. But in that game, if you can just optimize certain parts of the journey, you can make a big difference, right so way got a benign request from a marketer. Teo say, Listen, we do a lot of paid search. Can you help us with this one product? Just if you move it even like one percent, it would be significant to the company. But when? So okay, we'LL do that, >> and it worked out. We go in and help them do their >> search. But because we're thinking about experience in a broader sense for so well, let's let's do it more. Let's make them be able to transact or engage in multiple ways. Well, you could. You could sign up for the service to email. Or maybe there's click to call or click to chat. Or you could even walk into a branch and do it there. Maybe through the call centre, right? It's what's all that's working together on the channel, though fun words you want easy. You're leveraging >> different technologies to do it and people, >> so the way this worked was you were coming in through search and then eventually a lot of them were converting in the call center. So it was all working. And you think that's great? Well, it wasn't great to the company at all. They were very upset. The people that we're buying the media, we're really bummed because they couldn't get the attribution of the credit for the thing was in the call center. So they came over the great idea. They said, OK, take the phone number off and take the the click to call off and will force the >> customer to convert in. Our channel, of >> course, is a brilliant company with great people and rational thinking prevailed and they didn't do that. But they said, Well, what do we do? I said, Well, you're going to eat and multi attribution model to be able to help you do that, Okay, but that's not enough because you also need a new sales incentive and commission structure inside the call center because those people are getting pit on that. But since it's such a low commodity product, that's not gonna work to change. That's that's a new sales kind of thing, then you wait. They can't talk for another three seconds to that person because you'LL bring the margins on. You got to get him back. All the turtleneck just screwed up. That's right. So there's a new business process is now a new operating model whose skills to get him back into the general. So all of a sudden it's benign. Request from a marketing team taken, you optimize my paint search becomes new business transformation. Okay, now, because that brand manager had the guts to say I'm going to advocate for this customer. This customer wants to come in through this channel. They want to convert over here, and we're gonna actually change the operating model, the sales structure to call the sales lead. I had to call the CFO on the CEO, and we're gonna make this happen, Gonna change the way we do business on behalf of that customer. That is weight world, I could tell you we see this all the time and marketers all the time that there's so married to their website analytics funnel that that's all about who gets credit coded earls and the customer experience is a brutal. It's like I'm not here on other sites are all over the place. I don't really need to go the site every day, right? Somebody only go there when Otto and the thing we were talking about before. If you're grocery shopping >> and Europe's have set on Tuesday and you want to get off >> for your kid at versus the nice leisurely thing we talked about on the weekend, there's a whole nother set of outcomes in Cape Yas you have to deal with. If you went into that supermarket on Tuesday and they figured out a way to get you in and out fast and just get those two or three autumns, you need it for your kid. That's a failed trip. According to the grocery industry. You need to be in there longer they want, so you stay in the back. That's right. Totally. That breaks the whole model, but it's wonderful for you. You'LL shop there forever because of that experience, what you're getting at the Morrises air, changing the business models of cos that's the bottom line. You're at the center. That could be a driver for the transformation. That's it. Empathy. Is the driver Absolutely no. You need to have the emotional connection to all that stuff to help also internally see emos. I don't need to just be relevant and customers that need to be relevant to the enterprise. They need to be relevant to the CEO, Doc in seconds and hear the screaming and kicking and screaming right now. Glenn, that's great. But man, that's a heavy lift way could do it. How do you How do you get it? Because now I can see a cultural reaction. The antibodies will come out and attack that notion because it's scary because now, like, whoa, yeah, well, I mean, it is hard, but the good news is, is that we see, even at this conference, and a lot of our clients are coming over to do that this incremental ways to get there. But I'll make it simple. So the advantages are we said this new technology, new data that allow you to do some of this stuff right? That's great. And you can see a lot of them consolidating, right? A lot of the stacks all now have content and analytics and commerce and all that, and in this nice ways that they come together and that consolidation can help, and there's other ones that can handle different data sets, and that helps to his automation. And but the thing is that what people miss is one of the ways to accelerate this is add a human centered approach to how you actually create the experience internally. And what I mean is, it's not enough to consolidate the data and figure out that Gold nugget and not enough to do with technology have to do with humans. It's a human centered approach, so we're bringing in integrated teams of humans that are pulling all the stuff together. It's someone who understands strategy. Maybe someone understands creative when it hit me in the club, basically their prime in the pump getting it. But they will sit together. They sent to get the analytics. People sit next to the creative people. It's in next you people. They work on it as they designed the experience. You don't do a strategy project and then do a A road map and then do an R P for technology enabled Waterfall does not work, but it's beyond even waterfall versus algebra. This is actually taking humans and consolidate that thinking New skill sets at the center in like an incubator way to do pilots to do prototyping to do things. If you want to create that new experience that we're talking about in any of these cases, you gotta hand CMO some kind of thing that can bring to the team and say, Look, here's an app that would enable this or he has a pilot We could try without boiling the ocean toe, actually create an experience that would move the needle or whatever. Lame corporate analogy. Just make more money and get some decent results in Get a beachhead, just small eatery through it. Glenn. Great Insights. This is a great time. We'd love to get you back on the Cuban girl down, and it's kind of design thinking, combined with execution on the front lines with customers. Center the value proposition. Great conversation before we and just give a quick plug for the business. What's going on with a sensor Interactive? How's the business going? What are your goals? How many people are working there? What's the geography is looked like? Give us enough. Thanks for asking So essential Interactive is enjoying its third year as being listed by at H magazine, is the largest digital agency in the world on the fastest growing Wei have coverage and a truly integrated global delivery model that hits every part of the of every market. And we're so excited. Tio have this growth because it's a way to show that the market is truly interested and being experienced lead and the way we're defining experience. We're seeing more and more clients moving from some of these incremental changes to really >> try to put the customer at the center of what they're doing. And, you know, X Ensure Interactive believes in this model it is. It's very much in some ways way. Call it a new kind of provider, like an experience agency for lack of a better term. TTO help companies drive that transformation, and it's >> done with people and technology, and we're been on a tear recently. Most are growth is organic, but we also do lots and lots of acquisitions to make these capabilities come together. All the creativity and the design and the strategy and the techniques and the run of it is all in one integrated team, and that is very, very helpful when you're trying to do some of the things we've been talking about and you're you guys. I think I'm the right way. This customer wave is really, really because with digital customers air in charge, they control their data. They're now going to shift is happening. We're starting to see some visibility into it. It was going to impact the economics process and business models, so I think it's just beginning. Congratulations really is thanks. And we're so excited because some of the >> client successes it's truly transformational somethings. You got it. Carnival or Marriott or or Subway. I >> mean, it's a whole different >> kind of way of looking at experience, and it's >> really helping people. It's not just for its good for the business, but we're really changing people's lives and helping have experiences be meaningful. It's been wonderful and fun for us. Glenn, Thanks so much for sharing this insights here in the Cube. Hey, thanks for going the data Here live adobe summat. Twenty nineteen, Jumper, jefe Rick, Stay tuned for more coverage after this short break

Published Date : Mar 27 2019

SUMMARY :

Adobe Summit twenty nineteen brought to you by extension for interactive. So you guys are doing some great stuff around the creativity, peace, doing great customer experience. It's about creating, delivering and running the best experiences channels to direct to consumer, whether it be to be or be to see you and now have new to technology and data. and understanding ways to empathize with you in the moment and having experiences change marketing for years, and you can understand what they bought. me. You're empathizing in the moment with something that is meaningful that you care It's not about a better deal or I mean, to find the why is a holistic data sets, aunt have the mindset has to be a c M. O. And the key notes, you know, we're not a product company, not even really a service company. Now, the interesting thing of what you said is that And you can start to align products and services in that way, it's a good one, but the next one is really getting a little bit Mohr down to you. Saturday for your family and you're used to doing down your attitude. there to get the prescription, you're into speed and your stress in the moment they're versus. on Saturday you're like all try some new coupons and try some new things and go by. But the key thing to hear I mean, And what was the last time you guys were real excited about getting converted? Can you imagine? Well, I mean, the whole point of this is that when you really get into the mechanics So you have It's if you can just optimize certain parts of the journey, and it worked out. on the channel, though fun words you want easy. so the way this worked was you were coming in through search and then eventually customer to convert in. now, because that brand manager had the guts to say I'm going to advocate for this customer. We'd love to get you back on the Cuban girl down, you know, X Ensure Interactive believes in this model it is. All the creativity and the design and the strategy and the techniques and I It's not just for its good for the business, but we're really changing people's lives

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Harry Moseley, Zoom Video Communications | Enterprise Connect 2019


 

>> Live from Orlando, Florida its theCUBE covering Enterprise Connect 2019. Brought to you by Five9. >> Hello from Orlando, Lisa Martin with Stu Miniman theCUBE. We are live, day three at Enterprise Connect 2019. We have been in Five9's booth all week and we're very excited to welcome to the program for the first time Harry Moseley the CIO of Zoom Video Communications. Harry thanks so much for joining Stu and me on The CUBE today. >> Lisa, Stu its a pleasure to be here, thank you for having me. >> And you're a hall of famer, you have been inducted into the CIO Magazine's hall of fame and recognized as one of the world's top 100 CIO's be Computer World >> Yes that's right >> So we're in the presence of a VIP >> (chuckles) Well thank you for that it's, as I say its all credit back to the wonderful people that have supported me throughout my career. And I've worked with some amazing people and leaders and, who have supported me and the visions that I've created for their organizations. And so, I understand its about me but it's also about the great teams that I've worked with in my past. I can't make this stuff up, yep. >> Harry, we love talking to CIO's especially one with such a distinguished career as yours 'cause the role of CIO has gone through a lot of changes. IT has gone through a lot of changes. You know we've been doing this program for nine years. Remember reading Nick Carr's IT, does IT matter? And you know, we believe IT matters more than ever Not just IT, the business, the relationship maybe give us a little more of your view point as to the role of the CIO and technology, at a show like this. We hear about the CMO and the business and IT all working together. >> Yeah so its actually, in my opinion, there's never been a better time to be a CIO, irrespective of the company you are in, whether its a tech company like where I'm, you know Zoom Video Communications or any one of the prior companies I worked for, professional services, financial services. But even when you think about it like trucking, You think about trucking as an industry, you think about trucking as a company, its like it was a very sort of brick and mortars? But now its all about digital, right? A friend of mine runs a shipping container company and to think that they load five miles of wagons every day. And so I said to him, "how long does it take to load a wagon on a truck?" "It takes four minutes, and you know what Harry, "we're working that down to three. "And that'll increase our revenue by 20 to 25 percent.' And so its just fantastic. And the pace of change, you know it's just growing exponentially. It's just fascinating, the things that we can actually do today we only dreamed about them a year ago. And you think about it sort of' I can't wait to be back here next year, 'cause we're going to just lift the roof off this place in terms of the capabilities. And so its fantastic, yeah it's just absolutely fantastic. >> So looking at, a lot of us know Zoom for video conferencing and different things like that, but you said something very interesting in your fireside chat this morning that I hadn't thought about, and that is when, either going from audio to video, when you're on a video chat you really can't or shouldn't multi-task. So in terms of capturing peoples attention, enabling meetings to happen maybe more on time, faster, more productive. Thought that was an interesting realization, I thought, you're right. >> It just clicks, it just works. You know mobile, you know when I go back to my you know sort of' going back and again, thank you for the recognition from the key note. But when I go back earlier in my career it's like dialing that number, dialing that ten digit number, misdialing that number, what happened? I got to' hang up, I got to' get a dial tone, I got to' dial the numbers again. Now I'm like two minutes late and I know I'm late more often than I'd like, but when its late because of something like that, that's frustrating. That's really frustrating. And so the notion that you can just click on your mobile device, you can click on your laptop, I have no stress anymore, in joining meetings anywhere. I love telling the story about how I had a client meeting, I was in O'Hare Airport and I joined the client prospect meeting. I joined the prospect meeting on my phone using the free wifi service at O'Hare Airport. Put up my virtual background on my phone I just showed you this Stu, with our logo shared the content off of my phone 18 minutes into this 30 minutes call, the person I was talking to, the CIO for this firm called a halt to the meeting. This is what exactly what happened. Enough, I've heard enough. (announcement in background) >> Keep going. >> Keep going, okay. Enough, I didn't know what enough meant. And so I was a little spooked by that if you will. He goes, "you're on a phone, you're in O'Hare Airport, "you've got a virtual background, "you're sharing content, its all flawless. "Its like this is an amazing experience "that we can't get from all the technology "investment we've done in this space "for our company. "So guys, enough. "We're starting a proof of concept on Monday. "No more discussions about it. "Harry, looking forward to being a business partner." >> Does it get better than that? >> It doesn't get better than that. Its like you know, you hop through security, you get on a plane, and its cruisin' all the way home. >> Yeah I mean Harry, I do have to say, you know disclaimer, we are Zoom customers I'm actually a Zoom admin and its that simplicity that you've built into it is the experience, makes it easy. >> And then when you, and Stu, sorry to interrupt you but I got really excited about this stuff as you can tell. But, and then you look at the enterprise. So you're admin? You get into the enterprise management portal and its like Stu, I had a really bad experience. Oh let me look that up, oh yeah, okay. Where were you? You know, I was in outer Mongolia Ah okay, about five minutes into the call you had some packet loss, its like yeah it wasn't. But it still maintains the connection, right? So you can actually, so our Enterprise Management Portal is awesome. >> Yeah so that actually where I was going with the question, is you know I remember back, I actually worked for Lucent right after they spun out from AT&T. And we had videos talking about pervasive video everywhere, in my home in the business. Feels like we're almost there but still even when I have a team get together my folks that live in Silicon Valley, their connectivity's awful. You know when they have their, and its like oh well my computer or my phone don't have the cycles to be able to run. Maybe we have to turn off some of the video Are we getting there, will 5G solve some of these issues? Will the next generation of phones and computers keep up with it? Because it's, I'm sure you can guess we're big fans of video. It's a lot of what we do. >> Because video is the new voice, right. We like video. If I can only hear you and I can't see you, then when I make a statement I can't see you nodding. If I say something you like, you nod. So we get that concurrency of the experience Again it comes back Stu, where were we a year ago? The capabilities we had, where will we be a year from today? Whether its AI, whether its the power in the device in front of us whether its the network, you know, 5G is becoming a reality. It's going to take some time to get there but you've got sort of great technologies and capabilities, that you know, you look at the introduction of our real-time transcription services. I mean how cool is that? I'm sure there's lots of questions, so lots of people would ask about that real-time transcription in terms of, well what's next? I'm not going to talk about what's next. But as they say in life, watch this space. >> Yeah, just you made some announcements at the show with some partners I actually believe Otter AI is one of the ones you mentioned there. I got a demo of their thing, real time, a little bit of AI built in there. Can you talk about some of those partnerships? >> Yeah so we have great, we love our partnerships right? Whether its on the AI space, with Apple and Siri and Amazon and Otter. We also love our partnerships with Questron and Logitek and HP, and Polly of course. Again its the notion of, we have terrific software. You guys realize that, right? Its terrific software, proprietary QOS proprietary capabilities, its like its a fantastic experience every time on our software. These partners have great technologies too. But they're more on the hardware side, we are software engineers at our core. As Andreson said, I think it was about ten years go, "software is the easing thing in the world "so you take terrific software "you imbed it in terrific hardware "with terrific partners and what happens "is you get exceptional experiences." And that's what we want to deliver to people. So its not about the technology, its about the people. Its about making people happy, making easy, taking stress off the table. You go to the meeting, you light it up, you share the content, you record it, you can watch it later, its just terrific. >> So the people, the experiences you about we've been hearing that thematically for the last three days. As we know as consumers, the consumer behavior is driving so much of this change that has to happen, for companies to not just digitally transform, but to be competitive. We're in Five9's booth and they've mentioned they've got five billion minutes of recorded customer conversations. You guys can record, but its not just about the recording of the voice and the video and the transcription. Tell us about what you're doing to enable the context, so that the data and the recordings have much more value. >> Yeah so , I mean its the notion of being able to sort of rewind and replay. I'll give you another example if I may. Coming out of an office in Palo Alto jumped in the Uber, going back to San Jose for a client meeting. I'm a New Yorker as we talked about a few minutes ago and, I don't know the traffic patterns in Southern, in the Valley. And its about 5:00 o'clock, 5:15. San Jose meetings 5:45. Normally it would be fine, but its rush hour, what do I know about rush hour? I know a lot more now than then. I realize I'm not going to be able to make it on time. Put up the client logo, virtual background on the phone, in the Uber, client gets on the call, Harry where are you? I'm in the back of an Uber. Again, the same sort of experience. Then he asks the question, "well with this recording capability, "can I watch it at 35,000 feet?" Of course you can. And that was it. That was the magic moment for this particular client, because he said "I'm client facing all the time. "I don't get it in time, "I don't always make my management meetings "so I won't have to ask my colleagues what happened "and get their interpretation of the meeting. "I can actually watch the meeting "when I'm at 35,000 feet on a plane, going to Europe." So that's what this is all about. >> Alright, well Harry obviously this space excites you a bunch. Can you bring us back a little bit? This brought you out of retirement and the chase, the space is changing so fast. We come a year from now, what kind of things do we think we'll be talking about, and what's going to keep you excited going forward? >> So lets talk about the first part first and then sort of' break it into two. So yes I had a fantastic career and I retired and so when I met Eric and I met the leadership team at Zoom and I dug into the technology and I understood sort of' A, the culture of the company which is amazing. When I understood the product capability and how this was built as video first, and how we would have this maniacal focus if you will on sort of being a software company at our core. And how it was all about the people. That was sort of a very big part of my decision. So that was one. Two is, look we have a labor shortage right? We can't hire enough people, we can't hire the people, we have more jobs than we have people. So and so, retaining talent is really important. Giving them the technology and the studies that have been done, if you make an investment in the technology, that helps with retention. That helps with profit. It helps with, product innovation. So investment in the people. And the ability to collaborate. It's very hard to work if you don't collaborate, right? It just makes it really, very lumpy if you will. So the ability to collaborate locally, nationally, and globally, and people say, well what's collaborating locally? It's kind of like we can just walk down the corridor. Yeah, well if you're in two different buildings how do you get there? And then it gives us, a foot of snow between you, its makes it really hard. So collaborating locally, nationally, and globally is super important. So you put all that together that was the, what convinced me to say okay you know what, retirement, we're just going to put a pause button on that. And we're going to gave some fun over here. And that really has been, so I've, over a year now and its been absolutely amazing. So yes, big advances. What's in the the future? I think the future, you know there's been a lot of discussion around AI. We hear that its like, all the time. And we've seen from a variety of different providers this week in terms of their, their thoughts around how they're going to leverage AI. Its not about the technology, its about the end of the its about the user experience. And you look at the things that we started to do, we talked about real-time transcriptions a few moments ago, you look at the partnership that we have with Linkedin where you can hover over the name and their Linkinin profile pops up. You're going to see this, I just see this as an exponential change in these abilities. Because you have these building blocks today that you can grow on an exponential basis. So, the world is our oyster, is how I fundamentally think about it. And the art of the possible is now possible, And so lets, I think the future is going to' be absolutely amazing. Who would have, sorry Lisa, who would have thought a year ago, you could get on a plane using facial recognition? Let me just throw that out there. I mean, that's pretty amazing. Who would have thought a year ago that when you rent a car, you can just look at the camera on the way out and you're approved to go? Who would have thought that? >> So with that speed I'm curious to get your take on how Zoom is facilitating adoption. You mentioned some great customers examples where your engagement with them via Zoom Video Conference basically sold the POC in and of itself, with you at an airport >> That's a great questions. >> I guess O'Hare has pretty good wifi. >> What's that? >> O'Hare has pretty good wifi. >> A little choppy but, but it worked. >> It worked. >> Because of our great software, yeah. >> There you go, but in terms of adoption so as customers understand, alright our consumers are so demanding, we have to be able to react, and facilitate collaboration internally and externally. How, what are some of the tools and the techniques that Zoom delivers to enable those guys and gals to go I get it, I'm going to use it, And I'm actually going to actually use it successfully? >> This is a question, I don't know how many clients, CIOs, CTOs, C suite execs I talk to, and they all say, they all ask me similar sorts of questions. Like we're not a video first culture. Its like video, its kind of like we're a phone culture. And then I, so I throw that right back at them and I say and why is that? Because we don't have a good video platform. Aha. Now, when you have good video, when it just works when its easy, when its seamless, when its platform agnostic. IOS, Andriod, Mac, Windows, Linux, VDI, web. When you have this sort of, this platform when you're agnostic to the platform, and its a consistent high quality experience, you use it. So its the notion of, Lisa, it's the notion of would we rather get into a room and, would we rather get into a room and have a face to face meeting? Absolutely. So why would you get on a call and not like to see the people you're talking to. You like to see the people. Why, because its a video first. >> Unless its just one of those meetings that's on my calender and I didn't want to be there and I'm not going to listen. But I totally agree with you Harry. So, another hot button topic that I think we're at the center of here and that I'm sure you have an opinion on. Remote workers. So we watched some really big companies I think really got back in the dialogue a coupla' years ago when Yahoo was like okay, everybody's got to' come in work for us and we've seen some very large public companies that said you need to be in your workforce. and as I said, I'm sure you've got some pretty strong opinions on this >> I don't know what's going on here, quite honestly Stu but its like I think you're reading my brain because these are things I love talking about. So yeah, its. Sorry repeat the question? >> Remote workers. >> Remote workers, yeah. So first of all, I was at an event recently we talked about remote work. We didn't like the term. Its a distributed workforce. >> Yes. Because if you say you're a remote worker its kind like, that doesn't give you that warm feeling of being part of the organization. So we call it, so we said, we should drop calling people remote workers and we should call them a distributed work force. So that's one. Two is, I'm in New york, I'm in Orlando, I'm in Chicago, I'm in Atlanta, I'm in Denver. I'm on planes, I'm in an Uber. I don't feel disconnected at all. Why? Because I can see my colleagues, and its immersive. They share content with me. I'm walking down Park Avenue and I've got my phone and they're sharing content and I'm zooming in and I can see them and I can hear them and I'm giving feedback and I'm marking up on my phone, as I'm walking. So I don't feel, and then when I go to, its fascinating, and then I go to San Jose and I'm walking around the office and I'm seeing people physically. It doesn't feel like I haven't seen them, its really funny. I was in San Jose last week, Wednesday and Thursday in San Jose, took the red-eye back. Hate the red-eye but, I don't like flying during the day, I think it's inefficient, a waste of time. Took the red-eye back, now I'm on calls Friday morning from my office at home with my green screen, Zoom background and everybody's got, it's like I'm talking to the same people I was talking to yesterday but they were in the flesh, now they're on video. It's like Harry where are you, why didn't you come to the room? Well I'm back in New York. It's just just that simple, yep. >> That simple and really it sounds like Harry, what Zoom is delivering is a cultural transformation for some of these newer or older companies who, there is no reason not to be a video culture. We thank you so much for taking some time >> Thank you, thank you >> To stop by theCUBE and chat with Stu and me about all of the exciting things that brought you back into tech. and I'm excited to dial up how I'm using Zoom. >> Well we can take five minutes after this and I can show you some cool tricks >> Wow, from the CIO himself. Harry Moseley, thank you so much for your time. >> Thank you, thank you >> Great to have you on the program. For Stu Miniman, I'm Lisa Martin and you're watching theCUBE (upbeat tune)

Published Date : Mar 20 2019

SUMMARY :

Brought to you by Five9. the CIO of Zoom Video Communications. thank you for having me. (chuckles) Well thank you for that And you know, we believe IT matters more than ever And the pace of change, you know but you said something very interesting And so the notion that you can just click And so I was a little spooked by that if you will. and its cruisin' all the way home. I'm actually a Zoom admin and its that simplicity But, and then you look at the enterprise. with the question, is you know I remember back, I can't see you nodding. I actually believe Otter AI is one of the ones So its not about the technology, its about the people. So the people, the experiences you about jumped in the Uber, going back to San Jose and what's going to keep you excited going forward? and how we would have this maniacal focus if you will in and of itself, with you at an airport And I'm actually going to actually use it successfully? and its a consistent high quality experience, you use it. and that I'm sure you have an opinion on. Sorry repeat the question? We didn't like the term. its kind like, that doesn't give you that warm feeling We thank you so much for taking some time that brought you back into tech. Harry Moseley, thank you so much for your time. Great to have you on the program.

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Paul Martino, Bullpen Capital | CUBEConversation, February 2019


 

(upbeat music) >> Welcome to this special Cube Conversation. We're here in Palo Alto, California with a special guest. Dialing in remotely Paul Martino, the founder of Bullpen Capital and also the producer of an upcoming film called The Inside Game. It's a story about a true story about an NBA betting scandal. It's really, it's got everything you want to know. It's got sports, it's got gambling, it's got fixing of games. Paul Martino, known for being a serial entrepreneur and then an investor, investing in some great growth companies, and now running his own firm called Bullpen Capital, which bets on high-growth companies and takes them to the next level. Paul, great to see you. Thanks for spending the time. Good to see you again. >> John, always good to see you. Thanks for having me on the show. >> So, you're a unique individual. You're a computer science whiz, investor, entrepreneur, now film producer. This story kind of crosses over your interests. Obviously in Philly, you're kind of like me, kind of a blue collar kind of guy. You know hot starters when you see it. You also were an investor in a lot of the sports, gambling, betting, kind of online games, we've talked about in the past. But now you're crossing over into filming movies. Which is, seems like very cool and obviously we're living in a date of digital media where code is software, code is content, obviously we believe that. What's this movie all about? All the buzz is out there, Inside Game. You get it on sports radio all the time. Give us the scoop. Why Inside Game? What's it about? Give us the 411. >> Yeah, so John, I mean, this is a story that picked me. My producing partner in this is a guy named Michael Pierce who made a bunch of great movies, including The Cooler, one of the best gambling movies, with William H Macy. And he says sometimes the movie picks you and sometimes you pick the movie. And I wasn't sitting around one day going wow I want to be a movie producer, it was just much more that my cousin is the principal in the story. My cousin was the go-between between the gambler and the referee. The three of them were friends ever since they were kids. And when they all got out of jail Tommy called me, Tommy Martino. He said hey Paulie, you're about the only legitimate business guy I know. Could you help me with my life rights? And that's how this started almost six years ago. >> And what progressed next? You sat down, had a couple cocktails, beers, said okay here's how we're going to structure it. Was it more brainstorming and then it kind of went from there? Take us through that progression. >> It was a pure intellectual property exercise, and this is where being a startup guy was helpful. I was like, Tommy, I'll buy your life rights. Maybe we'll get a script written, we'll put it on the shelf, so that if anybody ever wants to make this story they have to go through us. Almost like a blocking patent or a copyright. And he's like okay cool. And so I said I have no delusions of ever making this movie. I actually don't know that, I don't know anybody to make a movie. This is not my skill set. But if anybody ever wants to make the movie, they're going to have to come deal with us. And then the lucky break happens, like anything in a startup. I have this random meeting with a guy named Michael Pierce, who was at a firm called WPS Challenger out of London. And we're down in Hillstone in Santa Monica, and I say to him, I say I've got this script written about this NBA betting scandal, would you do me a favor? He literally laughs in my face. He goes a venture guy from Silicon Valley is going to hand me a script. What a bad, anyway, I was like look dude, I'm a good guy to have owe you a favor so just read this dang thing. About 8 hours later my phone rings, he says who the hell is Andy Callahan? This is the best script I've ever read in my entire life. Let's go make a movie. Andy Callahan was a friend of a friend from high school who wrote the script. He actually once beat Kobe Bryant when he was a center at Haverford when Kobe Bryant played at Lower Merion here in the Philly suburbs. So, it's kind of this local Philly story. I'm a local Philly blue collar guy, we put the pieces together, and I'll be danged and now six years later the film is in the can and you're probably going to see it during the NBA finals this year in June. >> All right, so there's some news out there it's on the cover on ESPN Magazine, the site is now launched. I've been hearing buzz all morning on this in the sports radio world. A lot of buzz, a lot of organic virality around it. Reminds of the Crazy, Rich Asians, which kind of started organically, similar kind of community behind it. This has really got some legs to it. Give us some taste of what's some of the latest organic growth here around the buzz. >> Yeah so, think about this. This happened in, primarily '06 and '07. They were sentenced in 2010 and were in jail in 2011. It is 2019 and the front page story on ESPN is What Tim, Tommy, and Jimmy Battista Did. Those were the three guys, the gambler, the ref, and the go-between. And this is a front page story on ESPN all these years later. So we know this story has tremendous legs. We know this movie has a tremendous built-in audience. And so now it's just our job to leverage all those marketing channels, places we pioneered, like Zynga and FanDuel to get people who care about the story into the theaters. And we're hoping we can really show people how to do a modern way to market a film using those channels we've pioneered at places like FanDuel and Zynga. >> You and I have had many conversations privately and here on the Cube in the past around startups disruption, and it's the same pattern right? No one thinks it's a great idea, you get the rights to it, and you kind of got to find that inflection point, that magical moment which comes through networking and just hard work and hustle. And then you've got everything comes together. And then it comes together. And then it grows. As the world changes, you're seeing digital completely change the game on Hollywood. For instance, Netflix, you've got Prime, you've got Hulu. This is, essentially, a democratization, I'm not saying, well first of all you've made some money so you had some dough to put into it, but here's a script from a friend. You guys put it together. This is now the new startup model going to Hollywood. Talk about that dynamic, what's your vision there? Because this, I think, is an important signal in how digital content, whether it's guys in the Cube doing stuff or Cube Studios, which we'll, we have a vision for. This is something that's real. Talk about the dynamic. How do you see the entrepeneurial vision around how movies are made, how content's made, and then, ultimately, how they're merchandised in the future. >> Right, there's a whole, there's a whole bunch of buckets. There's the intellectual property bucket of the story, the script, etc. Then there's the bucket of getting the movie made. You know, that's the on the set and that's the director and that's post-production, and then there's the marketing. And what was really interesting is even though I'd never made a movie, two of those three buckets I knew a tremendous amount about from my experience as a startup investor. The marketing and the IP side I understood almost completely, even though I'd never made a film. And so all of the disruptive technologies that we learn for doing disruptive things like marketing a new thing called Daily Fantasy Sports, we were able to bring to bear to this film. Now, I had fun on the set and meeting all the actors, etc. But I had no delusion that I knew about the making of the movie part. So I plead ignorance there, but of the three buckets that you need to go make something in the media space 66% of what I knew as a startup guy overlapped and I think this is what the future of the media is. Because guys like me and you, John, we actually know a lot about this because we're startup people as opposed to we have to learn about it in terms of how to market and how to get an audience. I mean, my last company Aggregate Knowledge designs custom audiences for ad targeting. So we know how to find gamblers to go see this movie. That's literally the company I started. And so that's a thing that I'm very, very comfortable with and it's exciting to then work with the producer who did the creative and the director and I say hey guys, I've got this marketing thing under control, I know how to do it, oh by the way, the old Head of Marketing from FanDuel, he's a consultant to the project. Right, so, we got that. >> You got that, and the movie's being made. That's also again, back to entrepreneurship, risk. You got to take risks, right? This is all about risk management at the end of the day and you know, navigating as the lead entrepreneur, getting it done, there's heavy lifting and costs involved in making the movie, >> Right >> How did you, that's like production, right? You got to build a product. That is ultimately the product when it has to get to market. How did that go, what's your thoughts on your first time running a movie like this, from a production standpoint, learnings, observations? >> I learned a tremendous amount. I must admit, I was along for the ride on that piece of the puddle, puzzle. The product development piece of this was all new to me. But then again, I mean think about it, John, I started four companies, a social network, an ad targeting company, a game company, and a security company. I didn't know anything about those four companies when I started them either in terms of what the product needed to do. So learning a new product called make a movie was kind of par for the course, even though I didn't really know anything about it. You know, if you're going to be a startup person you got to have no fear. That's the real attribute you need to have in these kinds of situations. >> So I got to >> And so, witnessed that first-hand and, you know what, now, if I ever make a movie again I kind of know how to make that product. >> Yeah, well looking forward. You've got great instincts as an entrepreneur. I love hanging out with you. I got to ask you a question. I talk to a lot of young people, my son and his friends and I see people coming out of business school, all this stuff. You know, every college has an entrepreneurial program. Music, film, you know, whatever, they all have kind of bolted on entrepreneurship. You're essentially breaking down that kind of dogma of that you have to have a discipline. Anyone can do this, right? So talk about the folks that are out there, trying to be entrepreneurial, whether you're a musician. This is direct to consumer. If you have skills as an entrepreneur it translates. Talk about what it takes to be an entrepreneur, if you're a musician or someone who has, say, content rights or has content story. What do they do? What's your advice? >> We have lived through, perhaps the most awesome period of the last five to 10 years, where it got cheap to do a startup. You know, when we're doing our first startups 20 years ago, it cost 5 million bucks to go get a license from Oracle and go hire a DBA and do all that stuff. You know what, for 5 grand you can get your website up, you can build, you can use your iPhone, you can film your movie. That's all happened in the last five to 10 years. And what it's done is exactly the word you used. It's democratized who can become an entrepreneur. Now people who never thought entrepreneurship was for them, are able to do it. One of our great examples of this is Ipsy, our cosmetics company. You know, Michelle Phan was a cocktail waitress working in Florida, but she had this YouTube following around watching her videos of her putting her makeup on. And you know when we met her, we're like you know what? You're the next generation of what entrepreneurs look like. Because no, she didn't go to Stanford. She didn't have a PhD in computer science, but she knew what this next generation of content marketing was going to look like. She knew what it was to be a celebrity influencer. You know, that company Ipsy makes hundreds of millions of dollars every year now, and I don't think most people on Sand Hill would've necessarily given Michelle the chance because she didn't look like what the traditional entrepreneur looked like. So it's so cool we live in a time where you don't need to look like what you think an entrepreneur needs to look like or went to the school you had to think you'd go to to become an entrepreneur. It's open to everybody now. >> And the key to success, you know, again, we've talked about those privately all the time when we meet, but I want to get your comment on the record here. But I mean, there's some basic blocking and tackling that's independent of where you went to school that's being creative, networking, networking, networking, you know, and being, good hustle. And being, obviously good judgment and being smart. Do your thoughts on the keys to success for as those folks saying hey you know I didn't have to go to these big, fancy schools. I want to go out there. I want to test my idea. I want to go push the envelope. I want to go for it. What's the tried and true formula from your perspective? >> So when you're in the early stage of hustling and you want to figure out if you're good at being an entrepreneur, I tell entrepreneurs this all the time. Every meeting is a job interview. Now, you might not think it's a job interview, but you want to think about every meeting, this might be the next person I start my company with. This might be the person I end up hiring to go run something at my company. This might be the person I end up getting money for, from to start my company. And so show up, have some skills, have some passion, have a vision, and impress the person on the other side of the table. Every once in a while I get invited to a college and they're like well Paul, life's easy for you, you started a company with Mark Pinkus and you're friend with Reid Hoffman and this... Well how the hell do you think I met those people? I did the same thing I'm telling you to do. When I was nobody coming out of school, I went and did stuff for these guys. I helped them with a business plan. I wrote the code of Tribe, and then now all of the sudden we've got a whole network of people you can go to. Well, that didn't happen by accident. You had to show up and have some skills, talent, and passion and then impress the person on the other side of the table. >> Yeah >> And guess what? If you do that enough times in a row, you're going to end up having your own network. And then you're going to have kids come in and say, wow, how can I impress you? >> Be authentic, be genuine, hustle, do networking, do the job interview, great stuff. All right, back to final point I want to get your thoughts on because I think this is your success and getting this movie out of the gate. Everyone, first, everyone should go see Inside Game. Insidegamemovie.com is the URL. The site just went up. This should be a great movie. I'm looking forward to it, and knowing the work that went in, I followed your journey on this. It should be great. I'm looking forward to seeing it. Uh, digital media, um, your thoughts because we're seeing a direct to consumer model. You've got the big companies, YouTube, Amazon, others. There's kind of a, a huge distribution of those guys. The classic Web 2.0 search kind of paradigm and portal. But now you've got a whole 'nother set of distribution or network effects. Your thoughts, because you were involved in, again, social networking before it became the monster that it is now. How is digital media changing? What's your vision of how that's happening and how does someone jump on that wave and be successful? >> Yeah, we're in the midst of disruption. I mean, I'm in the discussions and final negotiations right now on how we're going to end up ultimately doing the film distribution. And I am very disappointed with the quality of the thinking of the people on the other side of the table. Because they come from very traditional backgrounds. And I'm talking to them about, I want to do a site takeover across Zynga. I want to do a digital download on FanDuel of a 20 minute clip of the film. And they're like what's FanDuel? Who's Zynga? And I'm sitting there, I'm like guys, this is the new media. Oh, by the way, there's a sports app called Wave and Wave is where the local influencers in the markets who want to write the stories are, and we want to do a deal with those guys. And oh, by the way, the CEO of that company is a buddy of mine I met years ago, right? One of those kids I gave advice to, and now I'm going to ask him for a favor from, right, that's how it works. But, it's amazing when you have these conversations with traditional old line media companies. They don't understand any of the words coming out of your mouth. They're like Paul, here's how much I'll give you for your film. Thank you, we'll go market it. I'm like, really? Seriously? I got the former CMO of FanDuel going to help out on this. You don't want to talk to him? >> Yeah >> And so this is where the industry is really ripe for disruption. Because the people from the startup world have already disrupted the apple cart and now we've just got to demonstrate that this model is going to continue to work for the future and be ready when the next new kind of digital transmedia thing comes along and embrace that, as opposed to be scared to death of it or not even know how to talk the language of the people on it. >> Well, you're doing some amazing venturing in your, kind of, unique venture capital model on Bullpen Capital. Certainly isn't your classic venture capital thing, so I'm sure people are going to be talking to you about oh, Paul, are all VCs going to be doing movies? I'm sure that's a narrative that's out there. But you're not just a normal venture capital. You certainly invest. So, venture capitals have reputation issues right now. People talk about, well, you know, they're group think. You know, they only invest in who they see themselves. You mentioned that comment there. The world's changing in venture. Your thoughts on that, how you guys started your firm, and your evolution of venture capital. And is this a sign that you'll see venture capitalists go into movies? >> Well, I don't know about that part. There have been a couple venture people who have done movies. But the part I will talk about is the you got to know somebody, it's an inside game, ha ha, we'll play double entendre on Inside Game here. You know, 20% of the deal we've done at Bullpen, we've done over 100. 20% of them were cold emails on something like LinkedIn or business plans at bullpen.com. 20%, now there's this old trope in venture if you don't get a warm intro I won't even talk to you. Well 20% of our deals came in and we had no idea who the person on the other side was. That's how we run the firm. And so if you're out there going I'm one of those entrepreneurs in the Midwest and no one, I don't know anyone. I'm not in a network, send me a plan. I'm someone who's going to look at it. It doesn't mean I'm going to be an investor, but you know what I'm going to do? I'm going to give you a shot. And I don't care where you're from or what school you went to or what social clique you're in or what your political persuasion is. Matter of fact, I literally don't care. I'm going to give you a shot. Come into my office and that, I think, is what was missing in a lot of firms, where it's a we only do security and we only look at companies that spun out of Berkeley and Stanford. And yeah, there can be an old boys network in that. But you know what, we like to talk to everybody. And the more blue collar the CEO is, the more we love them at Bullpen. >> That's awesome. Talk about the movie real quick on terms of how Hollywood's handling it. Um, expectations, in terms of reaction, was it positive, is it positive, what's the vibe going on in Hollywood, is this going to be a grassroots kind of thing around the FanDuels and your channels? What's your plan for that and what's the reaction of Hollywood? >> So it's going to be a lot of all of the above. But PR is going to be a huge component, I mean, part of the reason we're on today is there's a huge front page story on ESPN about Tim Donaghy and the NBA betting scandal of 2007. And so the earned media is going to be a huge component of this. And I think this is where the Hollywood people do understand the language we're speaking. We're like, look, we have a huge built-in audience that we know how to market to. We have a story. Actually, in the early days, you asked about risk? Back when I was thinking about if I would do this project I would do the following little market research. I'd walk into a sports bar, it didn't matter what town I was in. I could be in Dallas, I could be in Houston, I could be in Boston. I would literally walk up to the bar and say, hey, uh, six of you at the bar, ever hear of Tim Donaghy? It'd be amazing. About seven out of 10 people would go yeah he was the referee, crooked referee in the NBA. I'm like, this is amazing. Seven out of 10 people I meet in a bar know about the story I want to go tell. That sounds like a good chance to make a movie, as opposed to a movie that has no built-in audience. And so, a built-in audience with PR channels that we know work, I think we can really show Hollywood how to do this in a different way if this all works. >> And this comes back to my point around built-in audiences. You know, YouTube has got a million subscribers. That's kind of an old metric. That means they, like an RSS feed kind of model. That's a million people that are, could be, amplifying their network connections. It is a massive built-in audience. The iteration, the DevOps kind of mindset, we talk about cloud computing, can be applied to movies. It's agile movie making. That's what you're talking about. >> Yeah, and by the way, so we have a social network of all the actors and people in the film. So when it's ready, let's go activate our network of all the actors that are in the film. Each of them have a couple million followers. So let's go be smart. Let's, two weeks before the movie, let's send some screenshots. A week before the movie let's show some exclusive videos. Two days before the film, go see it, it's now out in the theaters. You know what, that's pretty, that's 101. We've got actors. We've got producers. Like, let's go use the influencer network we built that actually got the movie made. Let's go on Sports Talk, talk about the movie. Let's go on places like this and talk about how a venture guy made a movie. This is the confluence of all of the pieces all coming together at once. And I just don't think enough people in the film business or in the media business think big enough about going after these audiences. It's oh, we're going to take ads out on TV and I'm going to see my trailer and we're going to do this and that's how we do it. There's so many better ways to get your audience now. >> And this is going to change, just while I've got you here, it's just awesome, awesome conversation. Bringing it back to kind of the CMO in big companies, whether it's consumer or B to B or whatever, movies, the old model of here's our channels. There's certainly this earned media kind of formula and it's not your classic we've got a website, we're going to do all this instrumentation, it's a whole 'nother mechanism. So talk about, in your opinion, the importance of earned media, vis a vis the old other buckets. Owned media, paid media, well-defined Web 1.0, Web 2.0 tactics, earned media is not just how good is our PR? It's actually infrastructure channels, it's networks, a new kind of way to do things. How relevant and how important will this be going forward? Because there's no more website. It's a, you're basically building a media company for this movie. >> That is exactly right. We're building an ad hoc media business. I think this is what the next generation of digital agencies are going to look like. And there are some agencies that we've talked to that really understand all of what you've just said. They are few and far between, unfortunately. >> Yeah, well, Paul, this was theCube. We love talking to people, making it happen. Again, our model's the same as yours. We're open to anyone who's got signal, and you certainly are doing a great job and great to know you and follow your entrepreneur journey, your investment journey, and now your film making journey. Paul Martino, General Pen on Bullpen Capital, with the hot film Inside Game. I'm definitely going to see it. It should be really strong and it's going to be one of those movies like Crazy, Rich Asians, where not looking, not really well produced, I mean not predicted to be great and then goes game buster so I think this is going to be one of those examples. Paul, thanks for coming on. >> Love it, thank you! >> This Cube Conversation, I'm John Furrier here in Palo Alto, California, bringing ya all the action. Venture capitalist turned film maker Paul Martino with the movie Inside Game. I'm John Furrier, thanks for watching. (triumphant music)

Published Date : Feb 20 2019

SUMMARY :

and also the producer of an upcoming film Thanks for having me on the show. in a lot of the sports, And he says sometimes the movie picks you going to structure it. I'm a good guy to have owe you a favor Reminds of the Crazy, Rich Asians, It is 2019 and the and here on the Cube in the past but of the three buckets that you need and costs involved in making the movie, You got to build a product. That's the real attribute you need to have I kind of know how to make that product. I got to ask you a question. period of the last five to 10 years, And the key to success, you know, Well how the hell do you And then you're going to and knowing the work that went in, of the people on the of the people on it. to be talking to you about You know, 20% of the deal is this going to be a And so the earned media is going to be And this comes back to my point of all the actors and people in the film. And this is going to change, I think this is what the next generation and great to know you and follow your here in Palo Alto, California,

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Brandon Traffanstedt, CyberArk | AWS Marketplace 2018


 

>> From the ARIA Resort in Las Vegas, it's theCUBE. Covering AWS Marketplace. Brought to you by Amazon Web Services. >> Hey, welcome back here everybody Jeff Frick here with theCUBE. We are at AWS re:Invent 2018 wrapping up day one. We're going to do four days of coverage. We have four sets, three locations. But we're kicking things off here at the AWS Marketplace and Service Catalog event here at the ARIA. We're excited to be joined by our next guest, first time on theCUBE, but he's been working on the security stuff for a long time. He's Brandon Traffanstedt, he's the Global Director of System Engineering for CyberArk. Brandon, great to see you. >> Thank you very much. Glad to be here. >> Absolutely. So we started the conversation first off let's just give us the quick overview of CyberArk for people who are unfamiliar with the company. >> Definitely. So CyberArk does privilege access security, and that is the vaulting rotation in management of incredibly powerful accounts. Both traditional ones, the domain admin, to ones that exist in a more femoral, or cloud state. Access key, secret key pairs, route access into your console. So our goal is to take those out of the minds of users, out of those spreadsheets, out of hard coded code stacks. Place them in a secure location, rotate them, and then provide secure access to people as well as non people too. >> So you really segregate the privilege access as a very different category than just any regular user of kind of admin type of person. >> Absolutely. Though the focus is key. When we look the general spectrum of accounts in an organization, yes you've got the lower ones that are identity driven. Attackers might use those to get in, but really the creamy, nuggety center are those high value credentials. It's what brings down organizations. It's what we see involved in breaches every single day. So the focus there on those powerful ones is what gets us the most security posture increase with the least amount of effort. >> You know, it's interesting. 'Cause I always think of security as kind of like insurance. You can't absolutely be 100% positively. You can't spend every nickel you have on security, but you want to have a good ROI. So what you're saying, really, is this is a really good ROI investment from your security investment because these are really the crown jewels that you need to protect first. >> Absolutely. And like insurance, we often want to plan for the absolute worst to occur. There have been breaches in the past where yes, there were dollars that were spent on things like remediation, but if you have a huge customer base, even the postage alone to notify folks that you've had a compelling event tends to up into the seven figures. >> I never even thought of that. It's not a trivial expense. >> Absolutely. >> So, you said you've been doing this for 20 years, so a lot of change. There was no AWS re:Invent 20 years ago. There was not cloud computing as we know it today. So, you know we'll talk about kind of the current state but I'd love to get more kind of your historical perspective, you know being a security export, how your challenges have changed as this kind of continual escalation of war, accounting of strike counters strike. I'm thinking of MAD Magazine's Spy vs Spy, right, has continued to escalate over these 20 years. >> Definitely. So, years and years ago organizations were very monolithic from both the application side as well as their more kind of human focused infrastructure. Right, we had one or two domain controllers. Typically physical systems. But what happened is, the architecture broke down. So what, 10 years ago virtualization was the big thing, right. Same types of accounts, but more systems. More automation flows. So as we replaced humans with non humans, what happened was, more human users got over privileged, right? They were empowered to get their jobs done. But we had more and more robots that began doing their work. So one of the things that we saw, was the breaking down of the applications stacks to the point that we are now, you can spin up thousands of instances in a matter of clicks over a matter of seconds. Move that into a more micro services model, and you now have tens of thousands of nodes that can exist in the blink of an eye. All having the same type of access restrictions but just being far more distributed. >> Right. And so many more tax services with IOT, and all these things all over the place. And so, much more complex environment. >> Definitely. One of the things about all this beautiful automation and centralization that's occurring, is that now attackers don't have to go through that same type of flow they used to, right. Compromise an in user, escalate privilege on a laptop for instance, move laterally and continue to perform that dance. Now, all it takes is one compromise into your cloud management console for instance. And a lot of times that's game over. Our attacker is also changing a little bit. So I'm proud to say, but I'm a millennial and the thing about millennials is we tend to be very, some would say lazy, but I would say efficient in how we perform tasks. So for me, performing that lateral movement verses a one stop shop for a public effacing entity, I'm going to choose the one stop shop. >> Very true. So one of the hot topics in today's world is RPA, robotic process automation. We are at Automation Anywhere, we are at the UiPath Show this year, it's getting a lot of buzz. Both those companies have raised a ton of money. Hot, hot, hot space. It adds a whole new level of complexity and opportunity on the security side. So how should people be thinking about RPA and security? >> So when it comes to RPA, one of the things that is simply parr for the course, is that in order for robots to do their jobs, to build this automation that folks are looking for, they've got to authenticate this stuff. A lot of times we'll see that authentication happen as kind of an isolated secret that's stored, say inside of Automation Anywhere for instance. The goal there is, well we can rotate it, maybe, but now we have to update it here and there and a number of other spots. So one thing that we see as being a very prevalent theme is well let's find a centralized and secure source to manage them, and allow the robotic process automation to authenticate securely to that entity, pull the secrets as they need. Now, we can rotate that as many as what, ten, twelve times a day if we wanted to without our RPA missing a beat. At CyberArk we have what's called a C cubed alliance where we brought together a number of RPA vendors. All the ones that you mentioned. As well as other automation platforms, security vendors too. To where you don't have to do the work of integrating. It's already there and it's been built. And we're taking a huge direction from our customer base there to tell us what's hot, what's new for them. To let us proper those conversations. >> Because the robots are actually treated inside the system I believe, as like a person right? It's kind of like your own personal assistant. So in terms of the identity and the access, it's managed very much as if it was just a new hire. >> For sure. And if you look at it for instance using something like another automation platform like Jenkins. Jenkins is personified by a butler. Jenkins' task is to go out and perform all these tasks for you. But I'll submit to you if I were to offer you, hey Brandon, you can come to my house, vacuum my floor every Friday, that sounds like a pretty good deal. Especially if it's an open source. If I do it for you for free. But you encounter risk by giving me the keys to your house. The same is true for those automation platforms. A lot of times we divorce that robot from a human so we don't do the same level of due diligence to give the robot an identity to instantiate lease privilege. It's one of the things we've seen be a very huge theme in successful customer deployments. As well as automating their security too. >> Well at least they're not going to give away the security when someone calls up and says can you please give me the URL for the company picnic. I can't get in, you got to help me out. Hopefully they didn't train the robots to answer that question and let that social engineering enter. Is there social engineering for RPA? >> There is. When you look at RPA or even code that exists in public repositories, one of the quickest attacks you can do is to GitHub, search for your secret of choice. Maybe it's Postgres, maybe it's a vendor name underscore secret. If you sort that code by recent commits, you'll find people's hardcoded secrets that exist inside of public repositories. It's not because our developers are malicious. It's because it wasn't top of mind for them. They didn't have a more compelling solution. So that's one of the quickest attacks and I think that's social engineering. It could be as easy as compromising as say, one of your AWS administrators who happens to have a privileged key in a text file on his desktop. Same is also true there. >> Right Brandon, so we're here at the AWS Marketplace experience. Share with us a little bit about how you work with AWS Marketplace and what's that meant for your company. You've been around for 20 years. So you didn't need them to get started, but how are they helping you change your business? >> So one of the things that has been very top of mind for us over the past couple of years is supporting the community. In many cases folks will come to us with a project. Whether it be post breach mediation, audit compliance; whatever it may be, they have some indicator of moving forward. A lot of times when developers are building out processes, they may not be the driver from the business so the goal was we need to be able to support the community to provide open source secrets managements and do so very quickly. So there doesn't need to be a project or a red tape. AWS Marketplace has helped us provide our open source solution in a beautifully deployed package to as many folks as possible, so that at least they have some secure place to store those secrets without altering the way they do things. If they have to go outside of the Marketplace flows that they're used to, it's extra work. And we never want security to be a constraint to building good, quality automation development practices. >> Right. And how's Amazon been as a partner? There's a lot out there, be careful, they're going to see what you do and copy it and knock you out of business. How have they been working with as a partner? >> They've been fantastic. Highly supportive from both the programmatic secrets management perspective but also in providing best practices for how to deploy our core stack into AWS. How to handle things like auto scaling. As well as providing some APIs to extend our secrets management capability based on customer ASPs on both sides. >> Alright Brandon, well thank you for taking a few minutes. I'm sure we're both going to be dog tired in a couple of days. >> We can hope so, yeah. >> So we started while we were fresh. So I appreciate you taking a few minutes and stopping by. >> Always a pleasure. Thank you again for the invite. >> All right, he's Brandon, I'm Jeff. You're watching theCUBE. We're at AWS Marketplace and Service Catalog Experience here at the ARIA. Thanks for watching. See ya next time. (upbeat music)

Published Date : Nov 27 2018

SUMMARY :

Brought to you by Amazon Web Services. and Service Catalog event here at the ARIA. Glad to be here. So we started the conversation and that is the vaulting rotation in management So you really segregate the privilege access So the focus there on those powerful ones the crown jewels that you need to protect first. There have been breaches in the past It's not a trivial expense. but I'd love to get more kind of your historical So one of the things that we saw, And so many more tax services with IOT, and the thing about millennials is we tend to be very, So one of the hot topics in today's world All the ones that you mentioned. So in terms of the identity and the access, But I'll submit to you if I were to offer you, hey Brandon, the robots to answer that question one of the quickest attacks you can do So you didn't need them to get started, So one of the things that has been they're going to see what you do and copy it for how to deploy our core stack into AWS. Alright Brandon, well thank you for taking a few minutes. So I appreciate you taking a few minutes and stopping by. Thank you again for the invite. here at the ARIA.

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Anthony Di Iorio | Blockchain Futurist Conference 2018


 

(theCUBE theme music) >> Live from Toronto, Canada, it's theCUBE covering Blockchain Futurist Conference 2018. Brought to you by theCUBE. >> Hello everyone, welcome to the live coverage here in Toronto, this is theCUBE's coverage of Blockchain Futurist Event put on by Untraceable and the community here in Canada and around the world. I'm John Furrier with my cohost Dave Vellante, co founders of theCUBE, we're here with CUBE alumni, Anthony Di Iorio, who's the founder and CEO of Decentral and Jaxx, the really cool product we're going to get in to but also the co founder of Ethereum. Anthony, great to see you, thanks for coming back on theCUBE. >> Thanks for having me again. >> Great keynote, in typical Anthony Di Iorio fashion no slides, you decide what you're going to talk about before you get up on stage but you really kind of brought it- >> When I get on stage. >> When you get on stage, you come on, you do it. >> Yeah. >> But it's a nice theme, you're talking about the history, you're bringing in the community value. You talk about the key milestones. You're really recognizing what the community's done. But more importantly you're giving a roadmap of where you think the future's going and combined with the fact that you're also running Decentral and you got the Jaxx wallet so really cool. I want to ask you, where is it going and what's going on in the community from your perspective, as of today? >> So where is this entire space going? I think it's going to be revolutionary. I think the infrastructure is being built out now, it's been built out for the last number of years. I think we're seeing more and more the interfaces and the ways that the masses are going to start connecting with these technologies. We're still being hindered by some problems with scalability, some other problems that are stopping these technologies, these decentralized techs from really spreading globally and being able to be utilized in a way that's going to make things faster, better, and cheaper. But those problems will be solved and it's going to lead to revolutionary changes in every sector that you could imagine, every sector that relies on third parties and intermediaries to facilitate things, technology is going to emerge that's going to be able to make things better, make things faster. >> I want to ask you something because I'm seeing a trend happen. Obviously we've seen the cycle of prices drop and crypto prices and a lot of people are focused on the mechanics of coin price and so on and so forth. Also the international growth is pretty massive, but you're starting to see two types of swim lanes. One is get this thing, get this coin out there, get it trading, get token economics going and then you've got builders, building real products and durable companies, you're starting to see a trend now where people are starting to highlight the builders. People really looking at the longer term gain, trying to bring a token economics model but trying to get it right on building and this is kind of a critical kind of inflection point in the industry where it's not just, hey, I want to make some cash, there's actually economic benefits of this revolution. >> Yeah. >> But there's now a focus on the builders, people actually building technology, building companies. This is now the focus, this is what's becoming a legit deal, legit alpha entrepreneurs, real communities are galvanizing around that. Your reaction to that dynamic happening right now? >> It's what we've always tried to to. With my company, with Decentral, we're not banking on a token. There's no raising and taking people's money or token to grow and be the main focus of what we're doing. We may add a loyalty system in what we're doing down the road, but it would never be something that we're collecting money for, to actually make that as a main business. It's all about creating value and our goal is to create the interface for all projects to be able to have that ability to manage and move value in their different platforms. Our goal has always been to not rely on a token based system in order to create value and we're seeing more and more, that, I think, companies are realizing that you can have maybe some part of a token based system but you really have to create value with it and there's way too much idea of a token being the be all and end all and that's how we're going to base things and it's just there's too many of them out there right now and I think that creating a real value and not banking just on that token being where you're going to make money is probably, that's the building step that needs to get done. >> Well it's definitely a theme we've been hearing, "Too many damn tokens" and not enough value being created by those individual tokens. What's your take on the current sentiment? I mean obviously people have seen the crypto prices. Your thoughts on what's going on? >> There's just too much going on right now and that's a good thing. And there's a lot of competition but it's also very difficult to wade through al of the noise and wade through what's actually going to create value. Most of the stuff out there is not going to be valuable, it's not going to really radically- These companies and these projects that are emerging, not all of them are going to be successful and only a very few are actually going to create value so I find it very difficult as the time is passing to identify what is going to be actually good and there's just too much out there and it becomes very difficult to actually identify those things. >> Well somebody made the comment, we were doing a show yesterday here in Toronto and they said, "You know back then "there was really only one Vitalik Buterin "and now there's like zillions of him "and they're all creating amazing ideas "but there's a huge supply of those ideas." And to your point not all are going to succeed. >> It's ideas but it's about execution, too. >> Right. >> And really, can you carry that out? That's the hardest part, is execution and it's very difficult and there's a lot of people out there that struggle with that part. They have an idea, they've got a paper, they build a team and it's like, well how do we actually get it to create value? And then they're backing on their token value and they're not really creating something of substance that's going to be that value but it's also due to limitations that the space has right now and mostly with scalability. >> A big part of your effort is try to reduce some of that friction, right? I mean is that kind of the play? >> Yeah, our goal is to, when you build wallets or a project has to build their own wallet, it takes a lot of time, it takes a lot of effort and it's really not what their focus should be on. That's what our goal is, is to be that interface that projects can use to move and manage their digital currencies and connect them with other projects and other services that their user base needs. What's missing is those interfaces now and that's what has always been my focus. >> You said this, but when we interviewed you in the Bahamas we had a one on one, and also had a CUBE interview, but on the one on one you were basically saying the wallet's the new browser, which we like by the way, thought that was very relevant and we see the wallet dynamic being central. The other thing that we heard yesterday, and this has been a recurring them in the industry, is got to be easier to use. This whole system, it's like the internet. It's hard at first but then there's a chasm that's crossed on ease of use, that really will drive more adoption so the notion of the centrality of why the wallet is critical and also the ease of use because, like you said, entrepreneurs want to optimize their behavior, time to build value, not worry about prices of their coin and their velocity and float and stock prices when the reality is, there's work to be done. >> That's right, yeah. >> This is a real problem and there's opportunity, how is that wallet evolution going to emerge? How do you see it visa-vis potentially competition? What's your view now? Will there be a browser for every webpage or wallet for every- >> Well that's what I, I mean our goal is to be the single interface for all those projects and that's our goal. We want to be able to have and expedite the way that we can bring new projects on board. It's difficult right now because you have a lot of different technologies in the background that we have to integrate and connect with. Things with Ethereum are pretty simple, Bitcoin we've got, ones like Bitcoin but then there's all these new ones that are emerging, too and they require a lot more effort and resources to do. That is our next goal is how to expedite getting all this product in, because we want to be the single thing and it doesn't make sense that I've got a store or manage 20 different crypto currencies and I can only do some of them in Jaxx, I can do some of them across it, I got to use other systems. It's really not a great user experience and that's what we're trying to perfect. >> Yeah, so you really only want, as a user one or two browsers, you don't want- >> I'd say one browser is what you really want and that's pretty much, you would say Chrome is what people are mostly using now and that's what happens over time. >> Maybe a little bit of Safari for some other stuff, whatever, but you don't want four or five browsers. Nobody uses three or four browsers. So the browser is the metaphor that you've used. Some people have said, "Well, the better metaphor is the app". I got gazillions of apps on my phone. So help me understand why it's more browser than it is app. >> I would say that you have browsers that have apps and integrations in them, so Chrome has extensions, those are apps. The browser itself is basically it's an interface where you can see what's going on and allows you to move information. The wallet is what enables you to manage and move the value, and we have integrations so I consider those the apps that we'll have inside of the wallet that'll connect you to service providers that offer different value, different services. So I see it as the way for you to manage your keys and be able to navigate but the apps will be baked into the wallet, that will enable you to connect and buy and sell and trade and pay bills and all these things will be through apps so that's why I see that interface as the wallet, yeah. >> Talk about the dynamic around developers and one of the things that I've been saying on theCUBE and I'll say it here again, I think when you have volatility in pricing, that scares the market or whether it's people speculate whether it's being manipulated or not, doesn't matter. If there's a scare factor, developers are in it for the long game, right? When they pick a platform like Ethereum to work on, they're in it for the long haul so short term fluctuations shouldn't change behavior but there's now some dynamic where it kind of is and people are questioning that. What do you talk to those developers, saying stay the course, because Ethereum has the most developers, okay? By far. >> Yeah. >> What's the message to the developers? Don't worry, settle down, long game? >> Well they got to make their own decisions on that. I think that with, the industry is very market driven right now. Businesses, that are down to a fifth of what they were worth or what they have, you know just in a few months, really does take a toll. >> Yeah. >> And it really does, when you have a lot of growth plans and things you want to do, it really can put restrictions on that, so that's the world that it is in. As for developers, if they're passionate about what they're doing, especially with developers, they're generally going to do it, regardless of the money, I usually find. Some might leave, some might come in, but it's generally what the individual person's going to do. It's whether they should keep going on it but the markets, I mean the markets do really play a factor in a lot of things. How do you plan your 12 month ahead when the markets take you down to have such massive swing where you're now at 10% what you may have had. They really do play. >> You got to pay attention, their runway gets shortened big time >> So Anthony I was struck by your keynote today and other keynotes where I've seen you. You're incredibly humble, such a successful individual. You talk about your humble beginnings, the grassroots meet ups and I was struck by when you first read Vitaliks' "White Paper" you said it was very comp- after two or three pages you're like, "Eh" your eyes are bleeding so you went to Charles and he kind of explained things. >> Yeah. >> A lot of people feel like, okay you've got to be an alpha geek to succeed in this business. Talk about your particular skillset and maybe share with the audience some of the skillsets that they can tap to succeed in this industry. >> I hire a lot of developers, I am not a developer. I need to interface with them but I don't need to know a lot of the nitty gritty and if you have good people working for you on that end they don't want to be usually the ones that are leading stuff, they want to code and they want to do it so I've always been the person that can bring the team together and build a team that's going to be able to carry that out without me necessarily being the person that's doing that. You can't do everything. I am a generalist in a lot of different things. I am not very good at math. When Vitalik would write articles back in the day for Bitcoin Magazine, I would really read them and then he gets into his formulas and stuff and I'm, it's just not something I can do. I'm a generalist that does a number of different things and I can put the teams together and I can figure out ways to monetize and I can figure out ways to gather the right people together but I'm not a developer, I'm not a coder, and that's fine. I think it's the entrepreneurs that really are the ones that lead the things. I've always found I can hire developers. I think to have developers that are running projects? That's generally not their specialties, to be able to manage the whole operations or whole team and I think that's what Ethereum has suffered from since 2014. I think there was a, you know, we had eight founders split between developers and business people. It lead to a divide that eventually was turned into more of a developer focused project and that's where it's been since. What's that enabled is people such as myself, Joseph Lugen, Charles Hoskinson to do our own things and be able to do great things. And I think that you need a mixture of people with different sets of skills. And I think at the end of the day though, it's the vision of the entrepreneur, of the person that tasks the risks and is able to bring together all facets of something, not just necessarily the technical side or the developer side of things. >> What are the conditions that have made Toronto such an epicenter for blockchain development? >> I think it's mostly community. I think very early on, from the start of the meetups that I did and them growing and continuously doing them from 2012, 2013, 2014 to having people such as Vitalik being from here. Other entrepreneurs, there's just been a culture here blockchain here, that people have recognized and you're starting to see a lot of VCs a lot of people taking their trips up here and you're getting comments like, "Somethings happening "here in Toronto" and what's caused that and I think honestly a lot of it has to do with the meetups. I think be central and creating a physical hub that allowed the community to grow and start thinking about ideas and bringing people together, I think can put a lot of impact in it, has played a lot of that factor. >> A lot of talent, too, in here, too. >> And I think the talent, yeah, there's talent, but it's not just developers though, too. It's entrepreneurs. >> Yeah. >> Developers are one part of this animal and they're an important part but it's the idea that sparks risk taking and it's about putting together many pieces of the puzzle and developers are one aspect of it. I think it's more of the entrepreneurship that has actually created that. >> Yeah, cause there's a lot of talent in a lot of places. You know? >> I mean, I've been living in Silicon Valley for 20 years now, I moved from the east coast and it's a striking difference between the classic venture capital, Silicon Valley was where the action was in venture because of the ecosystem, the money capital formation, risk taking capabilities and people have tried to replicate Silicon Valley. Silicon Beach, Silicon this, Silicon that. But with blockchain and crypto token economics, for the first time the capital formation's different. The teams are forming in a different way where you're starting to see a re imagination of entrepreneurial epicenters and it's not trying to be Silicon Valley but the results still the same but that's what blockchain's all about, is re imagining something that can be done better, more efficiently. So you're starting to see Toronto, you're starting to see outside the United States with a lot of capital formation, lot of entrepreneurial energy, blockchain and crypto certainly has community. >> Yeah. >> Again, that's the perfect storm. This is impacting the entrepreneurial- >> It's also regulatory stuff as well. I think for Toronto, Canada to be doing what's it's done, in unregulatory uncertainty, like we don't know really what's going to happen here and that, I think, has stifled things to where it really could be because you do have a lot of companies here that will set up in a Caribbean country or set in Europe, they're setting up in Switzerland because they don't know the playing field of what they have to deal with here and that's something that's hindered things. It's the countries that figure that part out along with how do they spark and bring the entrepreneurs in and I think the regulatory climate plays a massive factor in that. We've been able to do in Toronto, Canada what we've been able to do, despite having the clarity and certainty in that space. >> That's a red flag I think that people should pay attention to, don't lose the entrepreneurial energy to another domicile, location. Alright, final question, at least for me, Dave might have one. As someone looking out over the landscape, certainly you've been involved on the business end and putting teams together on Ethereum, communities as well as your own company, looking out at the landscape, we spoke in February, at Poly Con, and going forward, what's the state of the union, in decentralization of applications and token economics and blockchain, what's your view of the current situation as the market is what it is now and certainly it's going to continue to evolve, what's the state of the union from Anthony Di Iorio's perspective? >> It's just keep doing what we're doing. Keep building things, keep building out infrastructure. I've toned down a lot of investments, I've toned down a lot of things to focus on that just because, A, it's very, very difficult now to distinguish between projects, it's very hard. B, I have a lot of investments which are going to grow over the next few years and my focus is now on doing my business stuff. I think we are going to weed out a lot of the people that aren't creating value in the space and that aren't going to be along for the ride so when they see the markets go down they're going to disappear but then they come back in and things are going to thrive. We've seen this before, it's not a new thing in this space. Things are going down, then they go higher then they go down, then they do higher again and it's been on generally a pretty good incline. We're just in the down thing right now, and that's okay, let's keep plugging away and keep building out infrastructure. >> Yeah and that's a clear theme you see here and other events, meetups. Unpinning optimism, right? It's still there, the innovation is still there. People are very excited. >> Do you think there's an emphasis on builders? I mean obviously you're just basically saying the value creators are going to be the center of the action. You think that the industry globally recognizes that the legit players creating value are the ones that are going to be rewarded and recognized? Are we not there yet, close enough? >> I don't know, that's an interesting question. I think eventually that's what's going to happen. >> Yeah. >> But I think right now there's a lot of people trying to make a lot of quick money. I think those people will be weeded out and I think it will come down to those value creators, those people that are really building things up that will be the ones that last, just like we saw with the internet, same type of thing, you have the hype, you have it grow, you have it blow up and then you have the slow, steady value added producers will be the ones that actually are going to be able to represent. >> Like you said, we've seen it before, it's jut a lot faster, a lot more compressed. >> All that happens over time, yeah. >> You determine how many cycles you live in this industry, you know we've talked about that before. Dave and I have been through many waves, as have you. Thanks so much for taking the time to come on. Give a quick plug on what's happening with Jaxx. Decentral, you had an amazing New York trip, your exclusive boat party was well talked about. You had the two cars you gave away but you laid out the future, 3.0, there's Jaxx wallet, you got some other projects. What's the status of Jaxx? How's it going and when can people get their hands on it and how are you onboarding customers? Give the update on the Jaxx wallet. >> Sure, so the Jaxx 2.0, called Jaxx Liberty is out in beta right now, you can download it on different platforms. What it is is an interface that does much more than just being a wallet. It's your charts, your graphs, your news, you portfolio, apps, it's gamified with leveling up experience points. We're going to connect you with our partners, all these different services, really to be the center point for that one single interface that you're going to have for everything, for your digital life. That's the goal for that, where you can be in control of your money, your identity, your communications and Liberty is coming out in the next couple weeks, the full release and that's really going to be our flagship product and I think it's going to be the thing that's going to create a single place for people to use in our space. >> Are developers going to be able to tap into this capabilities, as we as developers, will we be able to not only use the wallet will there be APIs and interfaces into the wallet? >> Yeah, so right now when we put integrations in what'll be coming over the next many months, will be us actually integrating with our partners but eventually our goal is to have STKs where you could use our back and infrastructures, our connections to blockchains, that we can give the tools to people, create their own utilities and their own applications inside of Jaxx. >> Well we certainly want to continue the conversation. Great to have you on, of course theCUBE token that we want for our media business, we want Jaxx on the wallet. >> Anthony Di Iorio, industry leader, pioneer, also running a great business, Decentral and Jaxx, here on theCUBE giving us the straight scoop, a shortcut to the truth. I'm John Furrier, Dave Vellante. Live coverage here in Toronto, part of Untraceable's flagship event here with all the best people in the blockchain industry, the Futurist Conference, we'll be right back with more after this short break. (theCUBE theme music)

Published Date : Aug 15 2018

SUMMARY :

Brought to you by theCUBE. and the community here in Canada and around the world. and combined with the fact that you're also and it's going to lead to revolutionary changes I want to ask you something This is now the focus, this is what's becoming and our goal is to create the interface I mean obviously people have seen the crypto prices. Most of the stuff out there is not going to be valuable, And to your point not all are going to succeed. that the space has right now and mostly with scalability. and it's really not what their focus should be on. but on the one on one you were basically saying I mean our goal is to be the single interface and that's pretty much, you would say Chrome So the browser is the metaphor that you've used. and allows you to move information. and one of the things that I've been saying on theCUBE that are down to a fifth and things you want to do, it really can put restrictions and he kind of explained things. and maybe share with the audience and build a team that's going to be able and I think honestly a lot of it has to do with the meetups. And I think the talent, yeah, and they're an important part but it's the idea Yeah, cause there's a lot of talent in a lot of places. and it's not trying to be Silicon Valley Again, that's the perfect storm. I think for Toronto, Canada to be doing and certainly it's going to continue to evolve, and that aren't going to be along for the ride Yeah and that's a clear theme you see here are the ones that are going to be rewarded and recognized? I think eventually that's what's going to happen. and then you have the slow, steady value added producers Like you said, Thanks so much for taking the time to come on. and I think it's going to be the thing that's going to but eventually our goal is to have STKs Great to have you on, of course theCUBE token a shortcut to the truth.

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Salman Asadullah, netnology.io | Cisco Live US 2018


 

>> Live from Orlando, Florida, it's The Cube, covering Cisco Live 2018. Brought to you by Cisco, Net App and The Cube's ecosystem partnership. >> Welcome back, we're here live at The Cube here in Orlando, Florida, for Cisco Live 2018. I'm John Furrier, Stu Miniman have been co-hosts all week here for three days live coverage. Day one and I'm winding down. Great keynotes, CEO of Cisco laying out the next generation network and it's not just the old networking, it's a whole nother thing. Our next guest is Salman Asadullah, who is the CTO and VP in Engineering at Netnology.io. Like technology, Netnology.io, former Cisco fellow been twenty- >> Distinguished engineer. >> Distinguished engineer, sorry, fellow engineer, well you look distinguished today. So how many years have you been at Cisco? >> 22 years. >> 22 years, welcome to The Cube. Thanks for joining us. >> Thank you for the invitation. >> So I got to ask you, before I get into the company, which we were talking before we came on camera, you doing really, I think you're on the front end of a big wave we see, certainly in The Cube, but you've been at Cisco 20 years and I've been working with Cisco since the beginning of time, 1993, in some capacity or another in the industry and I've had friends that have sold companies to Cisco. There's always been a debate within Cisco's engineering organization as to how to move up the stack. One team, yes no. So there's been but now it's time. Can you add some color and reaction to that because I think that's kind of where it is now. So all those conversations, even go back 15 years ago, where in the stack should we go? What's the right time? How about some of the history of Cisco and now they're moving up the stack. >> Yeah so I think first of all just to start with, our company name is Netnology.io but our tagline is full stack system integrator because we call ourselves a full stack system integrator because we know end networking, we know Cisco but we know how to move up in the stack as well. With the APIs and the STKs and what not. So the thing what is happened when you kind of look into this from Cisco's perspective, and I was there for 22 years, I am what I am because of Cisco, like when people say in Cisco when they work in Cisco I am Cisco but I still say I am Cisco because all of our business, 70% of our business is around Cisco. But the thing is when people are in Cisco, from Cisco's perspective when they say okay we are a software company and all of that good stuff, they look at the software from a networking perspective but the world, the industry when they say software, they are kind of talking about up in the stack from the application perspective. This is what you see even in Cisco they are sort of trying to pivot and all of the requisitions which are happening is around that. That they are acquiring companies which are basically up in the stack. There are more application based companies and also they are building organically some stuff in there as well. >> What's interesting is that the trend is their friend right now because they are getting to have their cake and eat it too. They are going to have best of both worlds. The networking is becoming more and more important with something to find and then you've got Kubernetes which Google Cloud is out there on the stage today. You've got Kubernetes and containers and Service Mesh is coming on that all look like networking. It's got words like policy, QOS, I mean this is networking world moving it up the stack. What does that mean for a customer? Is that the path in your mind? >> Yeah and I'm a big believer of that. I'm a big believer of that even before leaving Cisco for last five years of Cisco, I was basically working around all of these SDN, NFE, APIs and making sure in organizations I was leading or I was part of that how do I enable our engineering force to do some of that, to gain those capabilities. This is what we are trying to mimic on a much smaller scale in our company. That the way we sort of call it we are a bunch of hybrid engineers. The people who are CCIs but they can also code as well. This is our sort of a focus because just like what you said John, five years ago or three years ago when people talked about this stuff it was only about if you are a data center, cloud these things matter. But now, if you really see all Cisco's solutions are around APIs, around STKs, around SDN and NFE concepts. So let's say if you look into Cisco enterprise solution like SDA or SDVAN it's all around that. If you look into collaboration, Spark, Intropo it's all around that. So the point is that for any network, for any engineer or any organization to get to the next level they have to go through this evolution. >> And that's scaling too then. The network's got to scale and the new software environment. >> You bet. >> So there has been a big debate in the networking world, Salman, for many years, okay I ran networks, wait I have to be a coder. Maybe there's not that skillset. Will my solution providers and my software providers and the platforms I build on take care of some of that or is the traditional role of the network dead? You're saying your company's got a hybrid role but what percentage of people that are the CCIEs and the network admins today, how many of them need to be coding, developing, working with APIs and everything in the future? >> Yeah I think the way I sort of look at it that there's some push back. There is some push back but mainly more in the younger generation. They get it, they get it because if I give you an example of our company, we have 15 to 20 people company, the last two hires we had these were fresh grads, computer science grads and what I asked them to do, first six months go get your CCNA so then they start to understand some of the basics of the networking so they can work with our senior CCI engineers who know how to write 50 lines of five tone script but they can work with the coders to get bigger things developed. >> That's the new strategy from millennials. Throw them in CIE training, get them up to speed. Okay I got to ask you the question, because I want Netnology, the company that you're the co-founder of, is small but you're doing a unique thing. You're taking and SIE approach, obviously Cisco DNA is in your blood, you in the Cisco family if you will, but you still got to work with other platforms like Amazon and what not, as you guys go out there is a trend towards automation and we're seeing that professional services, whether they are from global SIs, the trend is towards accelerating down the cycle of deployment, faster, faster, faster, it's almost like the old days was eight months to roll out an SAP deployment, now that's eight weeks, now is it going to be eight minutes. This is the trend, it requires automation, what is your vision on how this is going to pan out going forward because this is the beginning of a new kind of Cloud scale at a service level. What's your vision? >> So if you really see from the compute world guys they were already doing that stuff for the longest time and they always asked us, the networking people, how come if my CAPEX is 30% but my OPPEX is 70% when it comes to the networking because we were lacking all of those capabilities. And the reason was that all the vendors they had these closed systems but now with this whole trend of SDN, NFE, people want to have more control. Cisco, and a lot of the vendors, they have all opened up their APIs and given the SD case so now you have the capability to go and take this talk to the compute guys. Say you are ahead of the game but we are catching up as well. By using all of these different tools what we are using in our deployments day in and day out. So if I give you an example, recently we did a project for a customer which was a multi-vendor fabric, VXLAN fabric, for data center, and we automated that whole deployment using Ansible Tower. So the thing is that if you would have done that manually, my God it would have taken a long time but now you can do it in minutes. >> Sal, talk about the Devnet explosion, because obviously we've reported all day today it came out in the keynote, over half a million developers are on Devnet, Susie Wee who's heading up Devnet and now Devnet Create which is the Cloud version of Devnet. Those two worlds are coming together and you're seeing network guys, even old school folks, adopting Cloud Navis. A natural migration and the younger guys are going and get networking as you pointed out. Devnet's been popular, you're seeing some great demos here. You can get a free Meraki Switch if you can code a little bit, take it home with you and play with it. A lot of tools, a lot of APIs as you're talking about, this is the new software development environment. What are you guys doing with Devnet? Can you share some insight into some of the things that you're doing that's relevant? Things that you're kicking the tires on? What's up? >> So first of all, to start with, we do a lot of work with Cisco Devnet and we are so humbled and honored by that because we get to learn while we are working on a lot of cool stuff. Then we can go sell that to our customers. Just to kind of tell you tomorrow, Susie Wee is announcing Devnet's cord exchange you might have heard about. So we are among those few partners who have contributed to that cord exchange. So we have put our code for everybody go get it, play with it, like we couple of use cases we have shared on that cord exchange, free for everybody. Think about you have Cisco VNFs running on AWFs how would you use cisco Cloud Center to model and deploy that service on AWFs? Using the APIs and then in the back end we have done scripting using Python and Shell and Ansible. These sort of things. And also we have a booth over here at the Devnet zone partner village and we are demonstrating some of these demos over there as well. >> That's really the standard now, people are getting the scale up in multiple clouds then deploying. That seems to be the big trend, automation there. >> Oh yeah, because as I said, the way we are partnered with Cisco we are also partnering with AWS and GCP so we have close to 35 certifications in our team including 13 CCIs. >> You're a veteran at Cisco, obviously to work at Cisco that long it's very entrepreneurial inside so it's always kind of been there. It's still a big company even when you were there but not you're an entrepreneur. What's it like on the other side? >> Oh my god, I'm living someone's dream. I'm blessed to be afford to do this. It's an awesome time for us. Of course it's a little stressful. >> Heavy lift there huh? It's not easy right? >> Me being in the silicon valley and I wanted to kind of do this but I tell you I recently Cisco included me in the Cisco designated VIP, which is a very selected group of people and worldwide, so I'm one of those people and I wrote a blog about that and I said something in there that although I have left Cisco but I don't feel like I've left Cisco because I'm still you know- >> Extended family. >> Yeah extended family. >> So what's up for the company, what's next? What's you're mission? Are you hiring? What are you working on? Share some insight into what's next for you guys? What's on your road map? >> So it's the growing pains. It's the growing pains, we are growing, our work is expanding. We are basically hiring some good talent. But more exciting something that we are also building a platform. So hopefully in the next six months we are going to be releasing something around that as well. Because again, think about we are recently named as a top 10 SDN providers by Enterprise Networking Magazine, so we are focusing on three Cisco SDN solutions. SDI in data center, SDA in branch and campus, and SDVAN on the VAN side. Now think about that you have segmentation in all of these solutions. How you can simplify this whole thing. How you can map these different perimeters between these three different solutions. So we are working on some cool ideas and some product as well so that's something really exciting for us. >> Are you guys self funded? >> Until now we are all privately funded. >> Sal, I'll put the hard question to you. As a startup, congratulations by the way, we know all about startups, we started a startup ourselves, it's growing pains but it's fun. It's hard work but it's a whole different joy. What problem are you solving? When you look at hiring an engineer what's the tough problem that you guys are trying to tackle? If you could boil it down into, the full stack great mission, what's the hard problem that you guys are trying to solve? >> So we just want to further simplify the Cisco story. As a matter of fact, in some of these SDN NFE based environments, that's our goal. How we can further simplify it. We are small enough that we can tackle some of these things. >> So tackle the complexity, that's where your mission is? >> Yes. >> Salman, thanks for coming on The Cube. Great to meet you, great to have you here. Thanks for sharing your insight here on The Cube with us live here- >> Very good, I appreciate the opportunity. >> Yeah let's follow up, love what you do. I think the future is going to be changing the game on how professional services are built, deployed and leveraged. Certainly code sharing. Collaboration is the new competitive behavior. You don't have to beat the other guy to win, you can work together. This is the new normal. This is what's going on at Cisco Live. Here in The Cube we're bringing you all the content. Stay with us, we'll see you tomorrow for day two of coverage. Thanks for watching.

Published Date : Jun 11 2018

SUMMARY :

Brought to you by Cisco, Net App and it's not just the old networking, So how many years have you been at Cisco? Thanks for joining us. another in the industry So the thing what is Is that the path in your mind? That the way we sort of the new software environment. and the network admins today, of the networking so they can work Okay I got to ask you the question, So the thing is that if you into some of the things Just to kind of tell you tomorrow, people are getting the the way we are partnered with Cisco What's it like on the other side? I'm blessed to be afford to do this. So hopefully in the next six months we Sal, I'll put the hard question to you. We are small enough that we can Great to meet you, great to have you here. the opportunity. the other guy to win,

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Pratima Rao Gluckman, VMware | Women Transforming Technology (wt2) 2018


 

(electronic music) >> Announcer: From the VMware campus in Palo Alto, California, it's theCUBE! Covering women transforming technology. >> Hi, welcome to theCube. Lisa Martin on the ground at the 3rd Annual Women Transforming Technology event at VMware in Palo Alto, and I'm joined by an author and a senior VMware engineer, Pratima Rao Gluckman. Welcome to the Cube, Pratima. >> Thank you, Lisa. It's great to be here >> It's great to have you here. So you have been an engineer here for about ten years. You knew from when you were a kid, love this, engineer, you knew you wanted to be that. You fell in love with your first programming class. It was like a Jerry McGuire, you complete me kind of moment I'm imagining. Tell me a little bit about your career in engineering and specifically as a female. >> Okay, so I was raised, born and raised, in India, and I grew up in an environment where I was gender blind. You know, my oldest sister played cricket for the country. >> Lisa: Wow! >> And it was a man's game! You know and a lot of people kind of talked about that, but it wasn't like she couldn't do it, right? So, I always grew up with this notion that I could do anything, and I could be whoever I wanted to be. And then I came to the United States, and that whole narrative stayed with me, the meritocracy narrative. Like you work hard, you know, society, the world will take care of you, and good things will happen, but it wasn't until 2016 was when I had this aha moment, and that's when I suddenly felt, suddenly I was aware of my gender, and I was like, okay I'm a female in tech, and there's lots of challenges for women in tech. And I didn't quite realize that. It was just that aha moment, and VMware has been a great company. I've been with VMware for nine years, I started as an engineer, and I moved into engineering management. We had Diane Greene who founded the company, the culture was always meritocratic, but I think something in 2016 kind of made me just thinking about my career and thinking about the careers of the women around me, I felt like we were stuck. But at the same time be focused on the women that were successful, for instance Yanbing Li, who's our senior VP and general manager of our storage business. And we were talking about her, and I said, this is what I said, I said, "There are some women who are successful despite everything "that we're dealing with, and I just want "to know their stories, and I'm going to write this book." The moment I said that it just felt right. I felt like this was something I wanted to do, and the stories in this book are inspiring stories of these women, just listening to Laila Ali this morning, her inspirational story, and this book has around 19 stories of these executive women, and they're just not role models, I mean every story offers strategies of how to thrive in the tech world. >> So interesting that first of all I love the title, Pratima, of this book, "Nevertheless She Persisted." So simple, so articulate, and so inspiring. So interesting, though, that you were working as an engineer for quite a few years before you realized, kind of looked around, like, whoa, this is a challenge that I'm actually living in. Yanbing is a CUBE alumni, I love her Twitter handle. So you said all right, I want to talk to some women who have been persistent and successful in their tech careers, as kind of the genesis of the book. Talk to us about, maybe, of those 19 interviews that range from, what, c-levels to VPs to directors. What are some of the stories that you found, what kind of blew your mind of, wow, I didn't know that you came from that kind of background? >> So when I started off I was very ambitious. I said I'd go interview CEO women, and I did a lot of research, and I found some very disturbing facts. You know, Fortune Magazine lists Fortune 500 companies, and they rank them based on their prior year's fiscal revenues, and from that data there were 24 women CEOs in 2014. That number dropped to 21 in 2015, and it dropped again in 2016, but it went up slightly in 2017 to 32 women, which is promising, but back in 2018 we're down to 24. So we have very very few women CEOs, and when I started off I said I'll talk to the CEO women, and I couldn't find any CEO women, my network, my friends' network, And so I dropped one level and I said let me go talk to SVPs and when I looked at VMware and VMware's network, Yanbing was one of them, so she's in the book, and then I reached out to contacts outside of my network. So I have some women from LinkedIn, I have Google, I have Facebook, I have some women from startups. So I have around four CEOs in the book, I've got, and what's great about this book is it's got a diverse set of women. Right? They have different titles; I've got directors, senior directors, VPs, Senior VPs, GMs, and CEOs. And some of them have PhDs, some of them have a Master's Degree, and some actually don't have formal training in computer science. I thought this would be interesting because a woman with any background can relate to it. Right? And so that was helpful. And so that's kind of how I went off and I started to write this book. And when I interviewed these women, there was a common theme that just kept emerging, and that was persistence. And they persisted against gender bias, stereotype threat, just the negative messages from media and society. I mean like Laila Ali was talking about just even the messages she got from her dad. >> Right. >> Right? Someone who was so close to her who basically said "Women can't box." And that didn't stop her; I mean she persisted. When I was listening to her, she didn't use the word, but, you know, she said she was believing in herself and all that, but she persisted through all those negative messages, right? And she said no one can tell her what to do. (laughs) >> Yeah her confidence is very loud and clear, and I think that you do find women, and I imagine some of them are some of the interviewees in your book, who have that natural confidence, and as you were saying when Muhammad Ali was trying to talk her out of it, and trying to, as she said, "He tried to get me think it was my idea," but she just knew, well no, this is what I want to do. And she had that confidence. Did you find that a lot of the women leaders in this book had that natural confidence? Like you grew up in an environment where you just believed "I can do this, my sister's playing cricket." Did you find that was a common thread, or did you find some great examples of women who wanted to do something, but just thought "Can I do this?" And "How do I do that?" What was the kind of confidence level that you saw? >> I was surprised because I had a question on imposter syndrome, and I asked these women, Telle Whiteney, who's the CEO, she was the CEO, ex-CEO >> Lisa: Grace Hopper >> Yes. The founder of Grace Hopper. I asked her about imposter syndrome and this is what she told me, she said "I feel like I'm not good enough" and that actually gave me goosebumps. I remember I was sitting in front of greatness and this is what she was telling me. And then I asked her "How do you overcome it?" and she said "I just show up the next day." And that actually helped me with this book because I am not an author. >> That's persistence. >> I mean I am an author now but 2 years ago when I started to write this, writing is not my forte. I'm a technologist, I build teams, I manage teams, I ship products, I ship technical products, but everyday I woke up and I said, "I'm feeling like an imposter." It was just her voice right? Yanbing also feels the same way, I mean she does feel times where she feels like, "I'm lacking confidence here." Majority of the people actually, pretty much all the women, this one woman, Patty Hatter, didn't feel like she had imposter syndrome but the rest of them face it everyday. Talia Malachi who's a principal engineer at VMWare, it's very hard to be a PE, she said that she fights it every day, and that was surprising to me, right? Because I was sitting in front of all these women, they were confident, they've achieved so much, but they struggle with that every day. But all they do is they persist, they show up the next day. They take those little steps and they have these goals and they're very intentional and purposeful, I mean just like what Layla said, right? She said, "Everything that I've done in the last 20 years "has been intentional and purposeful." And that's what these women did. And I learned so much from them because 20 years ago I was a drifter (laughs) you know I just kind drifted and I didn't realize that I could set a goal and I could reach it and I could do all these amazing things, and I didn't think any of this was possible for me. But I'm hoping that some girl somewhere can read this book and say "You know what this is possible", right? This is possible and you know role models, I think we need lots of these role models. >> We do I think, you know imposter syndrome I've suffered for it for so long before I even knew what it was and I'll be honest with you even finding out that it was a legitimate issue was (exhales) okay I'm not the only one. So I think it's important that you, that these women and youth are your voice, in your book, identified it. This is something I face everyday even though you may look at me on the outside and think, "She's so successful, she's got everything." And we're human. And Laila Ali talked about of having to revisit that inner lawyer, that sometimes she goes silent, sometimes the pilot light goes out and needs to be reignited or turned back up. I think that is just giving people permission, especially women, and I've felt that in the keynote, giving us permission to go, "Ah, you're not going to feel that everyday, "you're not going to feel it everyday." Get up the next day to your point, keep persisting and pursuing your purpose is in and of itself so incredibly empowering. >> Right but also imposter syndrome is good for you and I talk about that a little bit in the book. And you know why it's good for you? It's you getting out of your comfort zone, you're trying something different, and it's natural to feel that way, but once you get over it, you've mastered that, and Laila talked about it too today she said, "You get uncomfortable to the point "where you get comfortable." >> Lisa: Yes. >> So every time that you find that you have this imposter syndrome, just remember that greatness is right around the corner. >> Yep. I always say "Get uncomfortably uncomfortable". >> Pratima: Yes. >> And I loved how she said that today. So one of the big news of the day is VMWare with Stanford announcing that they are investing $15,000,000 in a new Women's Leadership Innovation Lab at Stanford. Phenomenal. >> Pratima: Yes. >> And they're really going to start studying diversity and there's so many different gaps that we face, wage gap, age gap, gender gap, you know mothers vs motherless gap, and one of the things that was really interesting that, I've heard this before, that the press release actually cited a McKinsey report that says, "Companies with diversity "on their executive staff are 21% more profitable." >> Yes. >> And that just seems like a, no duh, Kind of thing to me for organizations like VMWare and your other partners in this consortium of Wt Squared to get on board to say, "Well of course." Thought diversity is so important and it actually is demonstrated to impact a companies' profitability. >> Right, yeah. And that's true, I just hope that more people listen to it and internalize it, and organizations internalize that, and what VMWare's doing is fantastic. I mean I'm so proud to be part of this company that's doing this. And you Shelly talked about change right? She said, "I think, right now the way I feel "about this whole thing, is we need to stop talking about "diversity and inclusion, we just need to say "enough is enough, this is important, let's just do it." >> Lisa: We should make this a part of our DNA. >> Exactly. Just make it, why do we have to fight for all this, right? It's just pointless and you know, men have wives and daughters and mothers and you know, It impacts societies as a whole and organizations, and we have so much research on this and what I like about what the Stanford Research Lab is doing is, they're actually working with woman all the way from middle-school to high-school to the executive suite, and that's amazing because research has now shown, there was a report in March 2014 by a senior fellow at the Center for American Progress, for Judith Warner, and so she documented, just with the rate of change, like I talked with all the percentages and the number of women CEOs, just with that rate of change, the equality of men and women at the top will not occur until 2085. >> Lisa: Oh my goodness. >> That's 63 years from now. That means all our daughters would be retired by then. My daughters was born on 2013 and so she won't live in a world of female leaders that's representative of the population. And so that realization actually really, really, really broke my heart and that made me want to write this book, to create these role models. And what Stanford is doing, is they're going to work on this and I'm hoping that they can make that transition sooner. Like we don't have to wait 'till 2085. I want this for my daughter. >> It has to be accelerated, yes. >> It has to be accelerated and I think all of us need to do that, our daughters should be in the 20s, 30s when this happens, not when they're in their 70s. >> Lisa: And retired. >> And retired, I mean we don't want that. And we don't know how that number's going to get pushed further, right? Like if we don't do anything now... It. (exhales) >> Lisa: Right. 2085 becomes, what? >> I know! It's insane. >> In the spirit of being persistent, with the theme of this 3rd annual Wt Squared being Inclusion in Action, you're a manager and in a people or hiring role, tell me about the culture on your team and how your awareness and your passion for creating change here, lasting change. How are you actually creating that inclusion through action in your role at VMWare? >> So what I do is when I have to hire engineers on my team, I talk to my recruiter, have a conversation, I'm like, "I need more diversity." It's just not women, I want diversity with the men too. I want different races, different cultures because I believe that if I have a diverse team I'm going to be successful. So it's almost like I'm being selfish but that is very important. So I have that conversation with my recruiters, so I kind have an expectation set. And then we go through their hiring process and I'm very aware of just the hiring panel, like who I put on the panel, I make sure to have at least a women on the panel and have some diversity. My team right now is not really that diverse and I'm working hard to make that because it is hard, you know the pipeline has to get built at a certain point, and then start getting those resumes, but I try to have at least one female on the panel, and during the selection process the first thing I'll tell them is, let's get the elephant out of the room, age, gender, whatever, like let's take that out, let's just talk about skills and how well this person has done in an interview. And that's how I conducted and you know I've had fairly good success of hiring women on the team. But I've also seen that it's hard to retain women because they tend to drop-out faster than the men and so it's constant, it's just constant work to make that happen. >> Yeah. I wish we had more time to talk about retention because it is a huge issue. So the book is Nevertheless, She Persisted. Where can people get a copy of the book? >> So you can get it on Amazon, that's, I think, the best place to get it. You can also get it from my publisher's site which is FriesenPress. >> Excellent well Pratima thank you so much for stopping by. >> Thank you. >> And sharing your passion, how your persisting, and how you're also helping more of us learn how to find that voice and pursue our passions, thank you. >> Thank you. >> We want to thank you for watching. We are TheCUBE on the ground at VMWare for the Third Annual Women Transforming Technology Event. I'm Lisa Martin thanks for watching. (upbeat music)

Published Date : May 24 2018

SUMMARY :

Announcer: From the VMware campus and I'm joined by an author and a senior VMware engineer, It's great to be here It's great to have you here. and I grew up in an environment where I was gender blind. and the stories in this book are inspiring stories What are some of the stories that you found, and from that data there were 24 women CEOs in 2014. And that didn't stop her; I mean she persisted. and I think that you do find women, and I imagine and that actually gave me goosebumps. and that was surprising to me, right? sometimes the pilot light goes out and needs to be reignited and I talk about that a little bit in the book. just remember that greatness is right around the corner. And I loved how she said that today. that the press release actually cited a McKinsey report And that just seems like a, no duh, Kind of thing to me I mean I'm so proud to be part and the number of women CEOs, just with that rate of change, and that made me want to write this book, in the 20s, 30s when this happens, And retired, I mean we don't want that. I know! and how your awareness and your passion and during the selection process the first thing So the book is Nevertheless, She Persisted. the best place to get it. and how you're also helping more of us learn We want to thank you for watching.

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Blake Morgan, Author | CUBE Conversations Jan 2018


 

(lively music) >> Hello, and welcome to a special CUBE Conversation here in Palo Alto studios of theCUBE, I am John Furrier, the co-founder of SiliconANGLE Media and also the co-host of theCUBE. We are here with Blake Morgan, who is the futurist, author, speaker, around the concept of customer experience, and has a great new book out called, More is More. Blake, Welcome to theCUBE Conversation. >> Thank you John. >> Thanks for coming in. So I love that it is a hard cover book, the book is great, it feels good, the pages, it's a really good read, but it's got a lot of meaty topics in there. So let's just jump in, what's the motivation for the book? Why the book? Why More is More? >> So I have been in the contact center space for over 10 years and basically everyone under the sun is a customer and we all know what it feels like to have a bad customer experience. Have you had a bad customer experience ever? >> John: Oh yes. >> Yeah, right. >> So there is no shortage of work to be done in this space. I think now it's a great time to be in customer experience because there is more awareness about what it actually means. So, I wrote the book to basically provide some kind of definition and to really help people understand, What is customer experience?. Is it customer service? No, it's not. So what does it mean? How can businesses improve customer experience and what do they need to know to get started? >> How about the evolution? Because you know digital has really changed the game. You are seeing cloud computing, machine learning, AI techniques, bots certainly. I mean Twitter came out over ten years ago. I remember when Comcast Cares came out, you know that was a revolution. It was this one guy who decided to be on Twitter. We saw that beginning of that, that trend, where you can now serve and touch folks with customer service and experience, but then again, the blinds between customer experience and customer experience is blurring. Now those multiple channels, do you send them a Snapchat? Do you Instagram? All kinds of new things are emerging, so how do you define, as a frame, the customer experience in this new context? >> Yeah, you're right, there are so many channels. It's really overwhelming for a lot of businesses. So I think it is important to really cut out the noise to think about, Who are you as a business?, and Who is your customer?. What does your customer need? And I really encourage businesses to make their life harder to make it easier on the customer, because in so many situations, companies make it easier on themselves and make it harder on their customers. For example, say you do tweet a company, they might tell you, Hey, now you need to call us and repeat yourself or Now you need to send us an email. Well that's not easy for me as the customer. So it's really all about making customers' lives easier and better. That's the name of the game. >> So what was the findings in the book, when you did the research for the book, what was the core problem that companies are facing? Was it understanding customer experience? Was it the re imagining of customer experience? Was it just a strategic imperative? What was the problem that you uncovered that was the core to this new customer experience equation? >> So a lot of people equate customer experience with customer service and that's a big problem because for most companies, customer service is a cost center. It's not a revenue generating arm of the business. It's not exciting, it's not a money maker, it's not marketing or sales, and so that is really what people think of, when they think of customer experience. But the book is based on this DO MORE framework and DO MORE is basically represents as an acronym. Each piece of the six piece framework represents a different piece of where customer experience lives. So the first D is design something special. The second, I'm not going to read you every, I'm not going to bore you every single word, but the second is about loving your employees, so that is a part of it too. So culture, modernizing with technology, obsessing over your customers, having a culture of customer centricity and embracing innovation and disruption. So these are all varying pieces of DO MORE, which really helps companies understand, it's not simply something that sits in the contact center. For example, let's say you've got your laptop here, and you love your laptop, but your experience of the laptop is not only shaped by, say you have to contact the call center, it is also shaped by how that laptop was built and how about those people who built the laptop. Were they fighting at work with each other? Did they like their jobs? Did they like their boss? Honestly, that's going to impact your experience. >> Yeah, was it a sweat shop. >> Was it a sweat shop? There you go. >> I mean there's all kind of issues about social good too kind of comes into it with that. >> It actually does, I write a lot about social good in my book and some really great CEOs today get that social good is important, like the CEO of Patagonia or Marc Benioff. I mean you can just rattle off so many examples of stuff that he's doing, whether it is equal pay for woman, or his huge house in Hawaii where he's housed monks, to help them when one of the monks had cancer actually. Salesforce is constantly doing good for it's employees and for the community at large. >> Take me through your view on how executives should think about customer experience with all the digital transformation, because a lot of business models are shifting, you are seeing mobile apps, changing the financial services market, because now the app is the teller. So you have three kinds of companies out there, you've got the customer service oriented company, like a Zappos, or you've got a tech company like Google, but they are all about product innovation. Then you've got companies like Apple and others, that are like the big brand and culture personalities, so you've got these three different kind of companies as an example, each one might have a different view on customer experience. How do you tie, how does an executive figure out how to match the more into their DNA? >> That's a fantastic question. I think it's important to have somebody accountable to it, whether it's a Chief Customer Officer or your CMO, because the CEO is ultimately responsible, however, the CEO has their hand in so many things, it's not scalable for them to be so involved on a granular level, on customer centric metrics and so on and so forth throughout the organization. So I would encourage a company to actually hire somebody who is accountable, who creates even tiger teams across the organization with these customer centric metrics in mind, so everybody is working together and they know their job, no matter if they are HR or finance or marketing or customer service, that their metrics, their performance metrics, are tied back to the customer satisfaction. >> I know you do a lot of talks and you do a lot of speeches out there and events, what's the common question that you get? I mean what are people really struggling with or what are they interested in, what are some of the things that you are hearing when you are out on the road giving talks? >> I think it's hard to actually put some of these practices, I think it's actually hard to put some of these ideas into practice. For example, I recently gave a talk at a large technology company down here in San Jose and I presented some pretty wild ideas about actually the energy for influencing change. So how do we keep that high level of stamina with our employees when it's just quite hard to sometimes even keep up. I remember I gave this speech, I talked about a lot of very eccentric ideas about self-management, like when you are a worker you need to take care of yourself because the corporation is never going to give you a pass to let's say, rest, or do what you need to do to feel good, to be good at work. I noticed some of the people in the audience were all texting each other and afterwards someone came up to me and said, you know we are all texting each other because you say these things and the speech was purchased by the leader of the company, however, when it comes to actually working here, that is not really the vibe here, that's not the culture. So I think that a lot of, even the best companies today, still struggle every single day with some of these ideas, because when you DO MORE, when you work harder than others, it's tiring, it can take it's toll on employees. So how do you keep people fresh? >> So fatigue is a huge issue. >> Fatigue, yes. It is an issue. >> So how do they solve that? Because again, that is an experience and the employees itself represent brands. >> Yeah. >> So what are some of the solutions for that? >> Yeah so it's normal that people in these big companies feel fatigued when they are working harder for the customer, but it is really important for people to just manage themselves because no one is going to give you permission to take ten minutes to go for a walk, take ten minutes to go meditate, so it's really about management providing the room for employees to breathe and also modeling it as an example, if leaders just worked 24/7, it's all about the grind, the grind, the grind, that's not a healthy culture, so they need to push their people, but also give them some kind of safety that they can take care of themselves as well. >> So talk about the book target. Who is the ideal candidate for the book? Who are you writing the book for? What do you hope to accomplish for the reader and the outcome? >> So I write for Forbes and Harvard Business Review and Hemispheres Magazine, I have a lot of different types of readers because customer experience really affects everybody in business. So it could be the CMO, it could be the Chief Customer Officer, it could be the CEO, in fact the CEO of 1-800-Flowers wrote the foreword for my book, Chris McCann. So this book is really relevant for a wide variety of people who are interested in making their company more competitive. >> That's a great point, so let's trill down on that, customer experience just doesn't end in a department, we've seen this in IT, information technology, it's a department that becomes now pervasive with cloud computing, you see social media out there, so customer experience has multiple touch points, hence the broad appeal, how should someone think about being the customer experience champion? Because you always have the champions that kind of drives the change, so you've got change agents and you have kind of to me, the pre-existing management in place, what's the human role in this? Because remember, you have machines out there, you have bots, and all those machine learning technology out there, it's important that the human piece is integral to this, right? I mean what's your view on the role of the person? >> Yeah I'm not anti-technology, I'm not anti-bot, I am excited about the Amazon Go cashier-less stores, Amazon Go stores, but I do feel that technology can help us without totally replacing us. I think that we need thoughtful people in charge of these technologies to lead us, to make smart decisions, but you can't just let the technology go. I think that can be really scary. We've definitely seen so many TV shows about this, you can't blink without seeing another TV show about robots taking over the world. >> So it's a concern. What's the biggest thing you've learned from the book? What was the key learnings for you, personally, when you wrote this book? >> Well, writing a book, there is a lot of learning. I actually had my daughter, I was pregnant while I wrote this book and so I think for me to be totally candid, it was a lesson in patience and working through that period for me being pregnant. So I was like giving birth to the book and an actual baby. To be totally truthful, that was my learning. >> You got a lot more than the book. >> Blake: Laughing >> Well, congratulations, how old is the baby? >> She's sixteen months. >> Congratulations, awesome. >> Thank you. >> Well thanks for coming in and sharing about More is More, Blake Morgan, futurist author on the customer experience, More is More, it's theCUBE Conversation and really an impactful thought because customer experience transcends not just a department, it really is a mindset, it's about culture, it's about a lot of things, and it's certainly in the digital revolution, it's really going to be fundamental. Thanks for sharing your thoughts. >> Blake: Thanks so much. >> Appreciate it. I am John Furrier here in the Palo Alto studios for CUBE Conversation, thanks for watching. (lively music)

Published Date : Jan 26 2018

SUMMARY :

and also the co-host of theCUBE. the book is great, it feels good, the pages, So I have been in the contact center space I think now it's a great time to be in customer experience so how do you define, as a frame, to think about, Who are you as a business?, it's not simply something that sits in the contact center. There you go. I mean there's all kind of issues and for the community at large. So you have three kinds of companies out there, because the CEO is ultimately responsible, because the corporation is never going to give you a pass It is an issue. and the employees itself represent brands. to give you permission to take ten minutes to go for a walk, So talk about the book target. So it could be the CMO, I am excited about the Amazon Go cashier-less stores, What's the biggest thing you've learned from the book? and so I think for me to be totally candid, and it's certainly in the digital revolution, I am John Furrier here in the Palo Alto studios

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Data Science for All: It's a Whole New Game


 

>> There's a movement that's sweeping across businesses everywhere here in this country and around the world. And it's all about data. Today businesses are being inundated with data. To the tune of over two and a half million gigabytes that'll be generated in the next 60 seconds alone. What do you do with all that data? To extract insights you typically turn to a data scientist. But not necessarily anymore. At least not exclusively. Today the ability to extract value from data is becoming a shared mission. A team effort that spans the organization extending far more widely than ever before. Today, data science is being democratized. >> Data Sciences for All: It's a Whole New Game. >> Welcome everyone, I'm Katie Linendoll. I'm a technology expert writer and I love reporting on all things tech. My fascination with tech started very young. I began coding when I was 12. Received my networking certs by 18 and a degree in IT and new media from Rochester Institute of Technology. So as you can tell, technology has always been a sure passion of mine. Having grown up in the digital age, I love having a career that keeps me at the forefront of science and technology innovations. I spend equal time in the field being hands on as I do on my laptop conducting in depth research. Whether I'm diving underwater with NASA astronauts, witnessing the new ways which mobile technology can help rebuild the Philippine's economy in the wake of super typhoons, or sharing a first look at the newest iPhones on The Today Show, yesterday, I'm always on the hunt for the latest and greatest tech stories. And that's what brought me here. I'll be your host for the next hour and as we explore the new phenomenon that is taking businesses around the world by storm. And data science continues to become democratized and extends beyond the domain of the data scientist. And why there's also a mandate for all of us to become data literate. Now that data science for all drives our AI culture. And we're going to be able to take to the streets and go behind the scenes as we uncover the factors that are fueling this phenomenon and giving rise to a movement that is reshaping how businesses leverage data. And putting organizations on the road to AI. So coming up, I'll be doing interviews with data scientists. We'll see real world demos and take a look at how IBM is changing the game with an open data science platform. We'll also be joined by legendary statistician Nate Silver, founder and editor-in-chief of FiveThirtyEight. Who will shed light on how a data driven mindset is changing everything from business to our culture. We also have a few people who are joining us in our studio, so thank you guys for joining us. Come on, I can do better than that, right? Live studio audience, the fun stuff. And for all of you during the program, I want to remind you to join that conversation on social media using the hashtag DSforAll, it's data science for all. Share your thoughts on what data science and AI means to you and your business. And, let's dive into a whole new game of data science. Now I'd like to welcome my co-host General Manager IBM Analytics, Rob Thomas. >> Hello, Katie. >> Come on guys. >> Yeah, seriously. >> No one's allowed to be quiet during this show, okay? >> Right. >> Or, I'll start calling people out. So Rob, thank you so much. I think you know this conversation, we're calling it a data explosion happening right now. And it's nothing new. And when you and I chatted about it. You've been talking about this for years. You have to ask, is this old news at this point? >> Yeah, I mean, well first of all, the data explosion is not coming, it's here. And everybody's in the middle of it right now. What is different is the economics have changed. And the scale and complexity of the data that organizations are having to deal with has changed. And to this day, 80% of the data in the world still sits behind corporate firewalls. So, that's becoming a problem. It's becoming unmanageable. IT struggles to manage it. The business can't get everything they need. Consumers can't consume it when they want. So we have a challenge here. >> It's challenging in the world of unmanageable. Crazy complexity. If I'm sitting here as an IT manager of my business, I'm probably thinking to myself, this is incredibly frustrating. How in the world am I going to get control of all this data? And probably not just me thinking it. Many individuals here as well. >> Yeah, indeed. Everybody's thinking about how am I going to put data to work in my organization in a way I haven't done before. Look, you've got to have the right expertise, the right tools. The other thing that's happening in the market right now is clients are dealing with multi cloud environments. So data behind the firewall in private cloud, multiple public clouds. And they have to find a way. How am I going to pull meaning out of this data? And that brings us to data science and AI. That's how you get there. >> I understand the data science part but I think we're all starting to hear more about AI. And it's incredible that this buzz word is happening. How do businesses adopt to this AI growth and boom and trend that's happening in this world right now? >> Well, let me define it this way. Data science is a discipline. And machine learning is one technique. And then AI puts both machine learning into practice and applies it to the business. So this is really about how getting your business where it needs to go. And to get to an AI future, you have to lay a data foundation today. I love the phrase, "there's no AI without IA." That means you're not going to get to AI unless you have the right information architecture to start with. >> Can you elaborate though in terms of how businesses can really adopt AI and get started. >> Look, I think there's four things you have to do if you're serious about AI. One is you need a strategy for data acquisition. Two is you need a modern data architecture. Three is you need pervasive automation. And four is you got to expand job roles in the organization. >> Data acquisition. First pillar in this you just discussed. Can we start there and explain why it's so critical in this process? >> Yeah, so let's think about how data acquisition has evolved through the years. 15 years ago, data acquisition was about how do I get data in and out of my ERP system? And that was pretty much solved. Then the mobile revolution happens. And suddenly you've got structured and non-structured data. More than you've ever dealt with. And now you get to where we are today. You're talking terabytes, petabytes of data. >> [Katie] Yottabytes, I heard that word the other day. >> I heard that too. >> Didn't even know what it meant. >> You know how many zeros that is? >> I thought we were in Star Wars. >> Yeah, I think it's a lot of zeroes. >> Yodabytes, it's new. >> So, it's becoming more and more complex in terms of how you acquire data. So that's the new data landscape that every client is dealing with. And if you don't have a strategy for how you acquire that and manage it, you're not going to get to that AI future. >> So a natural segue, if you are one of these businesses, how do you build for the data landscape? >> Yeah, so the question I always hear from customers is we need to evolve our data architecture to be ready for AI. And the way I think about that is it's really about moving from static data repositories to more of a fluid data layer. >> And we continue with the architecture. New data architecture is an interesting buzz word to hear. But it's also one of the four pillars. So if you could dive in there. >> Yeah, I mean it's a new twist on what I would call some core data science concepts. For example, you have to leverage tools with a modern, centralized data warehouse. But your data warehouse can't be stagnant to just what's right there. So you need a way to federate data across different environments. You need to be able to bring your analytics to the data because it's most efficient that way. And ultimately, it's about building an optimized data platform that is designed for data science and AI. Which means it has to be a lot more flexible than what clients have had in the past. >> All right. So we've laid out what you need for driving automation. But where does the machine learning kick in? >> Machine learning is what gives you the ability to automate tasks. And I think about machine learning. It's about predicting and automating. And this will really change the roles of data professionals and IT professionals. For example, a data scientist cannot possibly know every algorithm or every model that they could use. So we can automate the process of algorithm selection. Another example is things like automated data matching. Or metadata creation. Some of these things may not be exciting but they're hugely practical. And so when you think about the real use cases that are driving return on investment today, it's things like that. It's automating the mundane tasks. >> Let's go ahead and come back to something that you mentioned earlier because it's fascinating to be talking about this AI journey, but also significant is the new job roles. And what are those other participants in the analytics pipeline? >> Yeah I think we're just at the start of this idea of new job roles. We have data scientists. We have data engineers. Now you see machine learning engineers. Application developers. What's really happening is that data scientists are no longer allowed to work in their own silo. And so the new job roles is about how does everybody have data first in their mind? And then they're using tools to automate data science, to automate building machine learning into applications. So roles are going to change dramatically in organizations. >> I think that's confusing though because we have several organizations who saying is that highly specialized roles, just for data science? Or is it applicable to everybody across the board? >> Yeah, and that's the big question, right? Cause everybody's thinking how will this apply? Do I want this to be just a small set of people in the organization that will do this? But, our view is data science has to for everybody. It's about bring data science to everybody as a shared mission across the organization. Everybody in the company has to be data literate. And participate in this journey. >> So overall, group effort, has to be a common goal, and we all need to be data literate across the board. >> Absolutely. >> Done deal. But at the end of the day, it's kind of not an easy task. >> It's not. It's not easy but it's maybe not as big of a shift as you would think. Because you have to put data in the hands of people that can do something with it. So, it's very basic. Give access to data. Data's often locked up in a lot of organizations today. Give people the right tools. Embrace the idea of choice or diversity in terms of those tools. That gets you started on this path. >> It's interesting to hear you say essentially you need to train everyone though across the board when it comes to data literacy. And I think people that are coming into the work force don't necessarily have a background or a degree in data science. So how do you manage? >> Yeah, so in many cases that's true. I will tell you some universities are doing amazing work here. One example, University of California Berkeley. They offer a course for all majors. So no matter what you're majoring in, you have a course on foundations of data science. How do you bring data science to every role? So it's starting to happen. We at IBM provide data science courses through CognitiveClass.ai. It's for everybody. It's free. And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. The key point is this though. It's more about attitude than it is aptitude. I think anybody can figure this out. But it's about the attitude to say we're putting data first and we're going to figure out how to make this real in our organization. >> I also have to give a shout out to my alma mater because I have heard that there is an offering in MS in data analytics. And they are always on the forefront of new technologies and new majors and on trend. And I've heard that the placement behind those jobs, people graduating with the MS is high. >> I'm sure it's very high. >> So go Tigers. All right, tangential. Let me get back to something else you touched on earlier because you mentioned that a number of customers ask you how in the world do I get started with AI? It's an overwhelming question. Where do you even begin? What do you tell them? >> Yeah, well things are moving really fast. But the good thing is most organizations I see, they're already on the path, even if they don't know it. They might have a BI practice in place. They've got data warehouses. They've got data lakes. Let me give you an example. AMC Networks. They produce a lot of the shows that I'm sure you watch Katie. >> [Katie] Yes, Breaking Bad, Walking Dead, any fans? >> [Rob] Yeah, we've got a few. >> [Katie] Well you taught me something I didn't even know. Because it's amazing how we have all these different industries, but yet media in itself is impacted too. And this is a good example. >> Absolutely. So, AMC Networks, think about it. They've got ads to place. They want to track viewer behavior. What do people like? What do they dislike? So they have to optimize every aspect of their business from marketing campaigns to promotions to scheduling to ads. And their goal was transform data into business insights and really take the burden off of their IT team that was heavily burdened by obviously a huge increase in data. So their VP of BI took the approach of using machine learning to process large volumes of data. They used a platform that was designed for AI and data processing. It's the IBM analytics system where it's a data warehouse, data science tools are built in. It has in memory data processing. And just like that, they were ready for AI. And they're already seeing that impact in their business. >> Do you think a movement of that nature kind of presses other media conglomerates and organizations to say we need to be doing this too? >> I think it's inevitable that everybody, you're either going to be playing, you're either going to be leading, or you'll be playing catch up. And so, as we talk to clients we think about how do you start down this path now, even if you have to iterate over time? Because otherwise you're going to wake up and you're going to be behind. >> One thing worth noting is we've talked about analytics to the data. It's analytics first to the data, not the other way around. >> Right. So, look. We as a practice, we say you want to bring data to where the data sits. Because it's a lot more efficient that way. It gets you better outcomes in terms of how you train models and it's more efficient. And we think that leads to better outcomes. Other organization will say, "Hey move the data around." And everything becomes a big data movement exercise. But once an organization has started down this path, they're starting to get predictions, they want to do it where it's really easy. And that means analytics applied right where the data sits. >> And worth talking about the role of the data scientist in all of this. It's been called the hot job of the decade. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. >> Yes. >> I want to see this on the cover of Vogue. Like I want to see the first data scientist. Female preferred, on the cover of Vogue. That would be amazing. >> Perhaps you can. >> People agree. So what changes for them? Is this challenging in terms of we talk data science for all. Where do all the data science, is it data science for everyone? And how does it change everything? >> Well, I think of it this way. AI gives software super powers. It really does. It changes the nature of software. And at the center of that is data scientists. So, a data scientist has a set of powers that they've never had before in any organization. And that's why it's a hot profession. Now, on one hand, this has been around for a while. We've had actuaries. We've had statisticians that have really transformed industries. But there are a few things that are new now. We have new tools. New languages. Broader recognition of this need. And while it's important to recognize this critical skill set, you can't just limit it to a few people. This is about scaling it across the organization. And truly making it accessible to all. >> So then do we need more data scientists? Or is this something you train like you said, across the board? >> Well, I think you want to do a little bit of both. We want more. But, we can also train more and make the ones we have more productive. The way I think about it is there's kind of two markets here. And we call it clickers and coders. >> [Katie] I like that. That's good. >> So, let's talk about what that means. So clickers are basically somebody that wants to use tools. Create models visually. It's drag and drop. Something that's very intuitive. Those are the clickers. Nothing wrong with that. It's been valuable for years. There's a new crop of data scientists. They want to code. They want to build with the latest open source tools. They want to write in Python or R. These are the coders. And both approaches are viable. Both approaches are critical. Organizations have to have a way to meet the needs of both of those types. And there's not a lot of things available today that do that. >> Well let's keep going on that. Because I hear you talking about the data scientists role and how it's critical to success, but with the new tools, data science and analytics skills can extend beyond the domain of just the data scientist. >> That's right. So look, we're unifying coders and clickers into a single platform, which we call IBM Data Science Experience. And as the demand for data science expertise grows, so does the need for these kind of tools. To bring them into the same environment. And my view is if you have the right platform, it enables the organization to collaborate. And suddenly you've changed the nature of data science from an individual sport to a team sport. >> So as somebody that, my background is in IT, the question is really is this an additional piece of what IT needs to do in 2017 and beyond? Or is it just another line item to the budget? >> So I'm afraid that some people might view it that way. As just another line item. But, I would challenge that and say data science is going to reinvent IT. It's going to change the nature of IT. And every organization needs to think about what are the skills that are critical? How do we engage a broader team to do this? Because once they get there, this is the chance to reinvent how they're performing IT. >> [Katie] Challenging or not? >> Look it's all a big challenge. Think about everything IT organizations have been through. Some of them were late to things like mobile, but then they caught up. Some were late to cloud, but then they caught up. I would just urge people, don't be late to data science. Use this as your chance to reinvent IT. Start with this notion of clickers and coders. This is a seminal moment. Much like mobile and cloud was. So don't be late. >> And I think it's critical because it could be so costly to wait. And Rob and I were even chatting earlier how data analytics is just moving into all different kinds of industries. And I can tell you even personally being effected by how important the analysis is in working in pediatric cancer for the last seven years. I personally implement virtual reality headsets to pediatric cancer hospitals across the country. And it's great. And it's working phenomenally. And the kids are amazed. And the staff is amazed. But the phase two of this project is putting in little metrics in the hardware that gather the breathing, the heart rate to show that we have data. Proof that we can hand over to the hospitals to continue making this program a success. So just in-- >> That's a great example. >> An interesting example. >> Saving lives? >> Yes. >> That's also applying a lot of what we talked about. >> Exciting stuff in the world of data science. >> Yes. Look, I just add this is an existential moment for every organization. Because what you do in this area is probably going to define how competitive you are going forward. And think about if you don't do something. What if one of your competitors goes and creates an application that's more engaging with clients? So my recommendation is start small. Experiment. Learn. Iterate on projects. Define the business outcomes. Then scale up. It's very doable. But you've got to take the first step. >> First step always critical. And now we're going to get to the fun hands on part of our story. Because in just a moment we're going to take a closer look at what data science can deliver. And where organizations are trying to get to. All right. Thank you Rob and now we've been joined by Siva Anne who is going to help us navigate this demo. First, welcome Siva. Give him a big round of applause. Yeah. All right, Rob break down what we're going to be looking at. You take over this demo. >> All right. So this is going to be pretty interesting. So Siva is going to take us through. So he's going to play the role of a financial adviser. Who wants to help better serve clients through recommendations. And I'm going to really illustrate three things. One is how do you federate data from multiple data sources? Inside the firewall, outside the firewall. How do you apply machine learning to predict and to automate? And then how do you move analytics closer to your data? So, what you're seeing here is a custom application for an investment firm. So, Siva, our financial adviser, welcome. So you can see at the top, we've got market data. We pulled that from an external source. And then we've got Siva's calendar in the middle. He's got clients on the right side. So page down, what else do you see down there Siva? >> [Siva] I can see the recent market news. And in here I can see that JP Morgan is calling for a US dollar rebound in the second half of the year. And, I have upcoming meeting with Leo Rakes. I can get-- >> [Rob] So let's go in there. Why don't you click on Leo Rakes. So, you're sitting at your desk, you're deciding how you're going to spend the day. You know you have a meeting with Leo. So you click on it. You immediately see, all right, so what do we know about him? We've got data governance implemented. So we know his age, we know his degree. We can see he's not that aggressive of a trader. Only six trades in the last few years. But then where it gets interesting is you go to the bottom. You start to see predicted industry affinity. Where did that come from? How do we have that? >> [Siva] So these green lines and red arrows here indicate the trending affinity of Leo Rakes for particular industry stocks. What we've done here is we've built machine learning models using customer's demographic data, his stock portfolios, and browsing behavior to build a model which can predict his affinity for a particular industry. >> [Rob] Interesting. So, I like to think of this, we call it celebrity experiences. So how do you treat every customer like they're a celebrity? So to some extent, we're reading his mind. Because without asking him, we know that he's going to have an affinity for auto stocks. So we go down. Now we look at his portfolio. You can see okay, he's got some different holdings. He's got Amazon, Google, Apple, and then he's got RACE, which is the ticker for Ferrari. You can see that's done incredibly well. And so, as a financial adviser, you look at this and you say, all right, we know he loves auto stocks. Ferrari's done very well. Let's create a hedge. Like what kind of security would interest him as a hedge against his position for Ferrari? Could we go figure that out? >> [Siva] Yes. Given I know that he's gotten an affinity for auto stocks, and I also see that Ferrari has got some terminus gains, I want to lock in these gains by hedging. And I want to do that by picking a auto stock which has got negative correlation with Ferrari. >> [Rob] So this is where we get to the idea of in database analytics. Cause you start clicking that and immediately we're getting instant answers of what's happening. So what did we find here? We're going to compare Ferrari and Honda. >> [Siva] I'm going to compare Ferrari with Honda. And what I see here instantly is that Honda has got a negative correlation with Ferrari, which makes it a perfect mix for his stock portfolio. Given he has an affinity for auto stocks and it correlates negatively with Ferrari. >> [Rob] These are very powerful tools at the hand of a financial adviser. You think about it. As a financial adviser, you wouldn't think about federating data, machine learning, pretty powerful. >> [Siva] Yes. So what we have seen here is that using the common SQL engine, we've been able to federate queries across multiple data sources. Db2 Warehouse in the cloud, IBM's Integrated Analytic System, and Hortonworks powered Hadoop platform for the new speeds. We've been able to use machine learning to derive innovative insights about his stock affinities. And drive the machine learning into the appliance. Closer to where the data resides to deliver high performance analytics. >> [Rob] At scale? >> [Siva] We're able to run millions of these correlations across stocks, currency, other factors. And even score hundreds of customers for their affinities on a daily basis. >> That's great. Siva, thank you for playing the role of financial adviser. So I just want to recap briefly. Cause this really powerful technology that's really simple. So we federated, we aggregated multiple data sources from all over the web and internal systems. And public cloud systems. Machine learning models were built that predicted Leo's affinity for a certain industry. In this case, automotive. And then you see when you deploy analytics next to your data, even a financial adviser, just with the click of a button is getting instant answers so they can go be more productive in their next meeting. This whole idea of celebrity experiences for your customer, that's available for everybody, if you take advantage of these types of capabilities. Katie, I'll hand it back to you. >> Good stuff. Thank you Rob. Thank you Siva. Powerful demonstration on what we've been talking about all afternoon. And thank you again to Siva for helping us navigate. Should be give him one more round of applause? We're going to be back in just a moment to look at how we operationalize all of this data. But in first, here's a message from me. If you're a part of a line of business, your main fear is disruption. You know data is the new goal that can create huge amounts of value. So does your competition. And they may be beating you to it. You're convinced there are new business models and revenue sources hidden in all the data. You just need to figure out how to leverage it. But with the scarcity of data scientists, you really can't rely solely on them. You may need more people throughout the organization that have the ability to extract value from data. And as a data science leader or data scientist, you have a lot of the same concerns. You spend way too much time looking for, prepping, and interpreting data and waiting for models to train. You know you need to operationalize the work you do to provide business value faster. What you want is an easier way to do data prep. And rapidly build models that can be easily deployed, monitored and automatically updated. So whether you're a data scientist, data science leader, or in a line of business, what's the solution? What'll it take to transform the way you work? That's what we're going to explore next. All right, now it's time to delve deeper into the nuts and bolts. The nitty gritty of operationalizing data science and creating a data driven culture. How do you actually do that? Well that's what these experts are here to share with us. I'm joined by Nir Kaldero, who's head of data science at Galvanize, which is an education and training organization. Tricia Wang, who is co-founder of Sudden Compass, a consultancy that helps companies understand people with data. And last, but certainly not least, Michael Li, founder and CEO of Data Incubator, which is a data science train company. All right guys. Shall we get right to it? >> All right. >> So data explosion happening right now. And we are seeing it across the board. I just shared an example of how it's impacting my philanthropic work in pediatric cancer. But you guys each have so many unique roles in your business life. How are you seeing it just blow up in your fields? Nir, your thing? >> Yeah, for example like in Galvanize we train many Fortune 500 companies. And just by looking at the demand of companies that wants us to help them go through this digital transformation is mind-blowing. Data point by itself. >> Okay. Well what we're seeing what's going on is that data science like as a theme, is that it's actually for everyone now. But what's happening is that it's actually meeting non technical people. But what we're seeing is that when non technical people are implementing these tools or coming at these tools without a base line of data literacy, they're often times using it in ways that distance themselves from the customer. Because they're implementing data science tools without a clear purpose, without a clear problem. And so what we do at Sudden Compass is that we work with companies to help them embrace and understand the complexity of their customers. Because often times they are misusing data science to try and flatten their understanding of the customer. As if you can just do more traditional marketing. Where you're putting people into boxes. And I think the whole ROI of data is that you can now understand people's relationships at a much more complex level at a greater scale before. But we have to do this with basic data literacy. And this has to involve technical and non technical people. >> Well you can have all the data in the world, and I think it speaks to, if you're not doing the proper movement with it, forget it. It means nothing at the same time. >> No absolutely. I mean, I think that when you look at the huge explosion in data, that comes with it a huge explosion in data experts. Right, we call them data scientists, data analysts. And sometimes they're people who are very, very talented, like the people here. But sometimes you have people who are maybe re-branding themselves, right? Trying to move up their title one notch to try to attract that higher salary. And I think that that's one of the things that customers are coming to us for, right? They're saying, hey look, there are a lot of people that call themselves data scientists, but we can't really distinguish. So, we have sort of run a fellowship where you help companies hire from a really talented group of folks, who are also truly data scientists and who know all those kind of really important data science tools. And we also help companies internally. Fortune 500 companies who are looking to grow that data science practice that they have. And we help clients like McKinsey, BCG, Bain, train up their customers, also their clients, also their workers to be more data talented. And to build up that data science capabilities. >> And Nir, this is something you work with a lot. A lot of Fortune 500 companies. And when we were speaking earlier, you were saying many of these companies can be in a panic. >> Yeah. >> Explain that. >> Yeah, so you know, not all Fortune 500 companies are fully data driven. And we know that the winners in this fourth industrial revolution, which I like to call the machine intelligence revolution, will be companies who navigate and transform their organization to unlock the power of data science and machine learning. And the companies that are not like that. Or not utilize data science and predictive power well, will pretty much get shredded. So they are in a panic. >> Tricia, companies have to deal with data behind the firewall and in the new multi cloud world. How do organizations start to become driven right to the core? >> I think the most urgent question to become data driven that companies should be asking is how do I bring the complex reality that our customers are experiencing on the ground in to a corporate office? Into the data models. So that question is critical because that's how you actually prevent any big data disasters. And that's how you leverage big data. Because when your data models are really far from your human models, that's when you're going to do things that are really far off from how, it's going to not feel right. That's when Tesco had their terrible big data disaster that they're still recovering from. And so that's why I think it's really important to understand that when you implement big data, you have to further embrace thick data. The qualitative, the emotional stuff, that is difficult to quantify. But then comes the difficult art and science that I think is the next level of data science. Which is that getting non technical and technical people together to ask how do we find those unknown nuggets of insights that are difficult to quantify? Then, how do we do the next step of figuring out how do you mathematically scale those insights into a data model? So that actually is reflective of human understanding? And then we can start making decisions at scale. But you have to have that first. >> That's absolutely right. And I think that when we think about what it means to be a data scientist, right? I always think about it in these sort of three pillars. You have the math side. You have to have that kind of stats, hardcore machine learning background. You have the programming side. You don't work with small amounts of data. You work with large amounts of data. You've got to be able to type the code to make those computers run. But then the last part is that human element. You have to understand the domain expertise. You have to understand what it is that I'm actually analyzing. What's the business proposition? And how are the clients, how are the users actually interacting with the system? That human element that you were talking about. And I think having somebody who understands all of those and not just in isolation, but is able to marry that understanding across those different topics, that's what makes a data scientist. >> But I find that we don't have people with those skill sets. And right now the way I see teams being set up inside companies is that they're creating these isolated data unicorns. These data scientists that have graduated from your programs, which are great. But, they don't involve the people who are the domain experts. They don't involve the designers, the consumer insight people, the people, the salespeople. The people who spend time with the customers day in and day out. Somehow they're left out of the room. They're consulted, but they're not a stakeholder. >> Can I actually >> Yeah, yeah please. >> Can I actually give a quick example? So for example, we at Galvanize train the executives and the managers. And then the technical people, the data scientists and the analysts. But in order to actually see all of the RY behind the data, you also have to have a creative fluid conversation between non technical and technical people. And this is a major trend now. And there's a major gap. And we need to increase awareness and kind of like create a new, kind of like environment where technical people also talks seamlessly with non technical ones. >> [Tricia] We call-- >> That's one of the things that we see a lot. Is one of the trends in-- >> A major trend. >> data science training is it's not just for the data science technical experts. It's not just for one type of person. So a lot of the training we do is sort of data engineers. People who are more on the software engineering side learning more about the stats of math. And then people who are sort of traditionally on the stat side learning more about the engineering. And then managers and people who are data analysts learning about both. >> Michael, I think you said something that was of interest too because I think we can look at IBM Watson as an example. And working in healthcare. The human component. Because often times we talk about machine learning and AI, and data and you get worried that you still need that human component. Especially in the world of healthcare. And I think that's a very strong point when it comes to the data analysis side. Is there any particular example you can speak to of that? >> So I think that there was this really excellent paper a while ago talking about all the neuro net stuff and trained on textual data. So looking at sort of different corpuses. And they found that these models were highly, highly sexist. They would read these corpuses and it's not because neuro nets themselves are sexist. It's because they're reading the things that we write. And it turns out that we write kind of sexist things. And they would sort of find all these patterns in there that were sort of latent, that had a lot of sort of things that maybe we would cringe at if we sort of saw. And I think that's one of the really important aspects of the human element, right? It's being able to come in and sort of say like, okay, I know what the biases of the system are, I know what the biases of the tools are. I need to figure out how to use that to make the tools, make the world a better place. And like another area where this comes up all the time is lending, right? So the federal government has said, and we have a lot of clients in the financial services space, so they're constantly under these kind of rules that they can't make discriminatory lending practices based on a whole set of protected categories. Race, sex, gender, things like that. But, it's very easy when you train a model on credit scores to pick that up. And then to have a model that's inadvertently sexist or racist. And that's where you need the human element to come back in and say okay, look, you're using the classic example would be zip code, you're using zip code as a variable. But when you look at it, zip codes actually highly correlated with race. And you can't do that. So you may inadvertently by sort of following the math and being a little naive about the problem, inadvertently introduce something really horrible into a model and that's where you need a human element to sort of step in and say, okay hold on. Slow things down. This isn't the right way to go. >> And the people who have -- >> I feel like, I can feel her ready to respond. >> Yes, I'm ready. >> She's like let me have at it. >> And the people here it is. And the people who are really great at providing that human intelligence are social scientists. We are trained to look for bias and to understand bias in data. Whether it's quantitative or qualitative. And I really think that we're going to have less of these kind of problems if we had more integrated teams. If it was a mandate from leadership to say no data science team should be without a social scientist, ethnographer, or qualitative researcher of some kind, to be able to help see these biases. >> The talent piece is actually the most crucial-- >> Yeah. >> one here. If you look about how to enable machine intelligence in organization there are the pillars that I have in my head which is the culture, the talent and the technology infrastructure. And I believe and I saw in working very closely with the Fortune 100 and 200 companies that the talent piece is actually the most important crucial hard to get. >> [Tricia] I totally agree. >> It's absolutely true. Yeah, no I mean I think that's sort of like how we came up with our business model. Companies were basically saying hey, I can't hire data scientists. And so we have a fellowship where we get 2,000 applicants each quarter. We take the top 2% and then we sort of train them up. And we work with hiring companies who then want to hire from that population. And so we're sort of helping them solve that problem. And the other half of it is really around training. Cause with a lot of industries, especially if you're sort of in a more regulated industry, there's a lot of nuances to what you're doing. And the fastest way to develop that data science or AI talent may not necessarily be to hire folks who are coming out of a PhD program. It may be to take folks internally who have a lot of that domain knowledge that you have and get them trained up on those data science techniques. So we've had large insurance companies come to us and say hey look, we hire three or four folks from you a quarter. That doesn't move the needle for us. What we really need is take the thousand actuaries and statisticians that we have and get all of them trained up to become a data scientist and become data literate in this new open source world. >> [Katie] Go ahead. >> All right, ladies first. >> Go ahead. >> Are you sure? >> No please, fight first. >> Go ahead. >> Go ahead Nir. >> So this is actually a trend that we have been seeing in the past year or so that companies kind of like start to look how to upscale and look for talent within the organization. So they can actually move them to become more literate and navigate 'em from analyst to data scientist. And from data scientist to machine learner. So this is actually a trend that is happening already for a year or so. >> Yeah, but I also find that after they've gone through that training in getting people skilled up in data science, the next problem that I get is executives coming to say we've invested in all of this. We're still not moving the needle. We've already invested in the right tools. We've gotten the right skills. We have enough scale of people who have these skills. Why are we not moving the needle? And what I explain to them is look, you're still making decisions in the same way. And you're still not involving enough of the non technical people. Especially from marketing, which is now, the CMO's are much more responsible for driving growth in their companies now. But often times it's so hard to change the old way of marketing, which is still like very segmentation. You know, demographic variable based, and we're trying to move people to say no, you have to understand the complexity of customers and not put them in boxes. >> And I think underlying a lot of this discussion is this question of culture, right? >> Yes. >> Absolutely. >> How do you build a data driven culture? And I think that that culture question, one of the ways that comes up quite often in especially in large, Fortune 500 enterprises, is that they are very, they're not very comfortable with sort of example, open source architecture. Open source tools. And there is some sort of residual bias that that's somehow dangerous. So security vulnerability. And I think that that's part of the cultural challenge that they often have in terms of how do I build a more data driven organization? Well a lot of the talent really wants to use these kind of tools. And I mean, just to give you an example, we are partnering with one of the major cloud providers to sort of help make open source tools more user friendly on their platform. So trying to help them attract the best technologists to use their platform because they want and they understand the value of having that kind of open source technology work seamlessly on their platforms. So I think that just sort of goes to show you how important open source is in this movement. And how much large companies and Fortune 500 companies and a lot of the ones we work with have to embrace that. >> Yeah, and I'm seeing it in our work. Even when we're working with Fortune 500 companies, is that they've already gone through the first phase of data science work. Where I explain it was all about the tools and getting the right tools and architecture in place. And then companies started moving into getting the right skill set in place. Getting the right talent. And what you're talking about with culture is really where I think we're talking about the third phase of data science, which is looking at communication of these technical frameworks so that we can get non technical people really comfortable in the same room with data scientists. That is going to be the phase, that's really where I see the pain point. And that's why at Sudden Compass, we're really dedicated to working with each other to figure out how do we solve this problem now? >> And I think that communication between the technical stakeholders and management and leadership. That's a very critical piece of this. You can't have a successful data science organization without that. >> Absolutely. >> And I think that actually some of the most popular trainings we've had recently are from managers and executives who are looking to say, how do I become more data savvy? How do I figure out what is this data science thing and how do I communicate with my data scientists? >> You guys made this way too easy. I was just going to get some popcorn and watch it play out. >> Nir, last 30 seconds. I want to leave you with an opportunity to, anything you want to add to this conversation? >> I think one thing to conclude is to say that companies that are not data driven is about time to hit refresh and figure how they transition the organization to become data driven. To become agile and nimble so they can actually see what opportunities from this important industrial revolution. Otherwise, unfortunately they will have hard time to survive. >> [Katie] All agreed? >> [Tricia] Absolutely, you're right. >> Michael, Trish, Nir, thank you so much. Fascinating discussion. And thank you guys again for joining us. We will be right back with another great demo. Right after this. >> Thank you Katie. >> Once again, thank you for an excellent discussion. Weren't they great guys? And thank you for everyone who's tuning in on the live webcast. As you can hear, we have an amazing studio audience here. And we're going to keep things moving. I'm now joined by Daniel Hernandez and Siva Anne. And we're going to turn our attention to how you can deliver on what they're talking about using data science experience to do data science faster. >> Thank you Katie. Siva and I are going to spend the next 10 minutes showing you how you can deliver on what they were saying using the IBM Data Science Experience to do data science faster. We'll demonstrate through new features we introduced this week how teams can work together more effectively across the entire analytics life cycle. How you can take advantage of any and all data no matter where it is and what it is. How you could use your favorite tools from open source. And finally how you could build models anywhere and employ them close to where your data is. Remember the financial adviser app Rob showed you? To build an app like that, we needed a team of data scientists, developers, data engineers, and IT staff to collaborate. We do this in the Data Science Experience through a concept we call projects. When I create a new project, I can now use the new Github integration feature. We're doing for data science what we've been doing for developers for years. Distributed teams can work together on analytics projects. And take advantage of Github's version management and change management features. This is a huge deal. Let's explore the project we created for the financial adviser app. As you can see, our data engineer Joane, our developer Rob, and others are collaborating this project. Joane got things started by bringing together the trusted data sources we need to build the app. Taking a closer look at the data, we see that our customer and profile data is stored on our recently announced IBM Integrated Analytics System, which runs safely behind our firewall. We also needed macro economic data, which she was able to find in the Federal Reserve. And she stored it in our Db2 Warehouse on Cloud. And finally, she selected stock news data from NASDAQ.com and landed that in a Hadoop cluster, which happens to be powered by Hortonworks. We added a new feature to the Data Science Experience so that when it's installed with Hortonworks, it automatically uses a need of security and governance controls within the cluster so your data is always secure and safe. Now we want to show you the news data we stored in the Hortonworks cluster. This is the mean administrative console. It's powered by an open source project called Ambari. And here's the news data. It's in parquet files stored in HDFS, which happens to be a distributive file system. To get the data from NASDAQ into our cluster, we used IBM's BigIntegrate and BigQuality to create automatic data pipelines that acquire, cleanse, and ingest that news data. Once the data's available, we use IBM's Big SQL to query that data using SQL statements that are much like the ones we would use for any relation of data, including the data that we have in the Integrated Analytics System and Db2 Warehouse on Cloud. This and the federation capabilities that Big SQL offers dramatically simplifies data acquisition. Now we want to show you how we support a brand new tool that we're excited about. Since we launched last summer, the Data Science Experience has supported Jupyter and R for data analysis and visualization. In this week's update, we deeply integrated another great open source project called Apache Zeppelin. It's known for having great visualization support, advanced collaboration features, and is growing in popularity amongst the data science community. This is an example of Apache Zeppelin and the notebook we created through it to explore some of our data. Notice how wonderful and easy the data visualizations are. Now we want to walk you through the Jupyter notebook we created to explore our customer preference for stocks. We use notebooks to understand and explore data. To identify the features that have some predictive power. Ultimately, we're trying to assess what ultimately is driving customer stock preference. Here we did the analysis to identify the attributes of customers that are likely to purchase auto stocks. We used this understanding to build our machine learning model. For building machine learning models, we've always had tools integrated into the Data Science Experience. But sometimes you need to use tools you already invested in. Like our very own SPSS as well as SAS. Through new import feature, you can easily import those models created with those tools. This helps you avoid vendor lock-in, and simplify the development, training, deployment, and management of all your models. To build the models we used in app, we could have coded, but we prefer a visual experience. We used our customer profile data in the Integrated Analytic System. Used the Auto Data Preparation to cleanse our data. Choose the binary classification algorithms. Let the Data Science Experience evaluate between logistic regression and gradient boosted tree. It's doing the heavy work for us. As you can see here, the Data Science Experience generated performance metrics that show us that the gradient boosted tree is the best performing algorithm for the data we gave it. Once we save this model, it's automatically deployed and available for developers to use. Any application developer can take this endpoint and consume it like they would any other API inside of the apps they built. We've made training and creating machine learning models super simple. But what about the operations? A lot of companies are struggling to ensure their model performance remains high over time. In our financial adviser app, we know that customer data changes constantly, so we need to always monitor model performance and ensure that our models are retrained as is necessary. This is a dashboard that shows the performance of our models and lets our teams monitor and retrain those models so that they're always performing to our standards. So far we've been showing you the Data Science Experience available behind the firewall that we're using to build and train models. Through a new publish feature, you can build models and deploy them anywhere. In another environment, private, public, or anywhere else with just a few clicks. So here we're publishing our model to the Watson machine learning service. It happens to be in the IBM cloud. And also deeply integrated with our Data Science Experience. After publishing and switching to the Watson machine learning service, you can see that our stock affinity and model that we just published is there and ready for use. So this is incredibly important. I just want to say it again. The Data Science Experience allows you to train models behind your own firewall, take advantage of your proprietary and sensitive data, and then deploy those models wherever you want with ease. So summarize what we just showed you. First, IBM's Data Science Experience supports all teams. You saw how our data engineer populated our project with trusted data sets. Our data scientists developed, trained, and tested a machine learning model. Our developers used APIs to integrate machine learning into their apps. And how IT can use our Integrated Model Management dashboard to monitor and manage model performance. Second, we support all data. On premises, in the cloud, structured, unstructured, inside of your firewall, and outside of it. We help you bring analytics and governance to where your data is. Third, we support all tools. The data science tools that you depend on are readily available and deeply integrated. This includes capabilities from great partners like Hortonworks. And powerful tools like our very own IBM SPSS. And fourth, and finally, we support all deployments. You can build your models anywhere, and deploy them right next to where your data is. Whether that's in the public cloud, private cloud, or even on the world's most reliable transaction platform, IBM z. So see for yourself. Go to the Data Science Experience website, take us for a spin. And if you happen to be ready right now, our recently created Data Science Elite Team can help you get started and run experiments alongside you with no charge. Thank you very much. >> Thank you very much Daniel. It seems like a great time to get started. And thanks to Siva for taking us through it. Rob and I will be back in just a moment to add some perspective right after this. All right, once again joined by Rob Thomas. And Rob obviously we got a lot of information here. >> Yes, we've covered a lot of ground. >> This is intense. You got to break it down for me cause I think we zoom out and see the big picture. What better data science can deliver to a business? Why is this so important? I mean we've heard it through and through. >> Yeah, well, I heard it a couple times. But it starts with businesses have to embrace a data driven culture. And it is a change. And we need to make data accessible with the right tools in a collaborative culture because we've got diverse skill sets in every organization. But data driven companies succeed when data science tools are in the hands of everyone. And I think that's a new thought. I think most companies think just get your data scientist some tools, you'll be fine. This is about tools in the hands of everyone. I think the panel did a great job of describing about how we get to data science for all. Building a data culture, making it a part of your everyday operations, and the highlights of what Daniel just showed us, that's some pretty cool features for how organizations can get to this, which is you can see IBM's Data Science Experience, how that supports all teams. You saw data analysts, data scientists, application developer, IT staff, all working together. Second, you saw how we support all tools. And your choice of tools. So the most popular data science libraries integrated into one platform. And we saw some new capabilities that help companies avoid lock-in, where you can import existing models created from specialist tools like SPSS or others. And then deploy them and manage them inside of Data Science Experience. That's pretty interesting. And lastly, you see we continue to build on this best of open tools. Partnering with companies like H2O, Hortonworks, and others. Third, you can see how you use all data no matter where it lives. That's a key challenge every organization's going to face. Private, public, federating all data sources. We announced new integration with the Hortonworks data platform where we deploy machine learning models where your data resides. That's been a key theme. Analytics where the data is. And lastly, supporting all types of deployments. Deploy them in your Hadoop cluster. Deploy them in your Integrated Analytic System. Or deploy them in z, just to name a few. A lot of different options here. But look, don't believe anything I say. Go try it for yourself. Data Science Experience, anybody can use it. Go to datascience.ibm.com and look, if you want to start right now, we just created a team that we call Data Science Elite. These are the best data scientists in the world that will come sit down with you and co-create solutions, models, and prove out a proof of concept. >> Good stuff. Thank you Rob. So you might be asking what does an organization look like that embraces data science for all? And how could it transform your role? I'm going to head back to the office and check it out. Let's start with the perspective of the line of business. What's changed? Well, now you're starting to explore new business models. You've uncovered opportunities for new revenue sources and all that hidden data. And being disrupted is no longer keeping you up at night. As a data science leader, you're beginning to collaborate with a line of business to better understand and translate the objectives into the models that are being built. Your data scientists are also starting to collaborate with the less technical team members and analysts who are working closest to the business problem. And as a data scientist, you stop feeling like you're falling behind. Open source tools are keeping you current. You're also starting to operationalize the work that you do. And you get to do more of what you love. Explore data, build models, put your models into production, and create business impact. All in all, it's not a bad scenario. Thanks. All right. We are back and coming up next, oh this is a special time right now. Cause we got a great guest speaker. New York Magazine called him the spreadsheet psychic and number crunching prodigy who went from correctly forecasting baseball games to correctly forecasting presidential elections. He even invented a proprietary algorithm called PECOTA for predicting future performance by baseball players and teams. And his New York Times bestselling book, The Signal and the Noise was named by Amazon.com as the number one best non-fiction book of 2012. He's currently the Editor in Chief of the award winning website, FiveThirtyEight and appears on ESPN as an on air commentator. Big round of applause. My pleasure to welcome Nate Silver. >> Thank you. We met backstage. >> Yes. >> It feels weird to re-shake your hand, but you know, for the audience. >> I had to give the intense firm grip. >> Definitely. >> The ninja grip. So you and I have crossed paths kind of digitally in the past, which it really interesting, is I started my career at ESPN. And I started as a production assistant, then later back on air for sports technology. And I go to you to talk about sports because-- >> Yeah. >> Wow, has ESPN upped their game in terms of understanding the importance of data and analytics. And what it brings. Not just to MLB, but across the board. >> No, it's really infused into the way they present the broadcast. You'll have win probability on the bottom line. And they'll incorporate FiveThirtyEight metrics into how they cover college football for example. So, ESPN ... Sports is maybe the perfect, if you're a data scientist, like the perfect kind of test case. And the reason being that sports consists of problems that have rules. And have structure. And when problems have rules and structure, then it's a lot easier to work with. So it's a great way to kind of improve your skills as a data scientist. Of course, there are also important real world problems that are more open ended, and those present different types of challenges. But it's such a natural fit. The teams. Think about the teams playing the World Series tonight. The Dodgers and the Astros are both like very data driven, especially Houston. Golden State Warriors, the NBA Champions, extremely data driven. New England Patriots, relative to an NFL team, it's shifted a little bit, the NFL bar is lower. But the Patriots are certainly very analytical in how they make decisions. So, you can't talk about sports without talking about analytics. >> And I was going to save the baseball question for later. Cause we are moments away from game seven. >> Yeah. >> Is everyone else watching game seven? It's been an incredible series. Probably one of the best of all time. >> Yeah, I mean-- >> You have a prediction here? >> You can mention that too. So I don't have a prediction. FiveThirtyEight has the Dodgers with a 60% chance of winning. >> [Katie] LA Fans. >> So you have two teams that are about equal. But the Dodgers pitching staff is in better shape at the moment. The end of a seven game series. And they're at home. >> But the statistics behind the two teams is pretty incredible. >> Yeah. It's like the first World Series in I think 56 years or something where you have two 100 win teams facing one another. There have been a lot of parity in baseball for a lot of years. Not that many offensive overall juggernauts. But this year, and last year with the Cubs and the Indians too really. But this year, you have really spectacular teams in the World Series. It kind of is a showcase of modern baseball. Lots of home runs. Lots of strikeouts. >> [Katie] Lots of extra innings. >> Lots of extra innings. Good defense. Lots of pitching changes. So if you love the modern baseball game, it's been about the best example that you've had. If you like a little bit more contact, and fewer strikeouts, maybe not so much. But it's been a spectacular and very exciting World Series. It's amazing to talk. MLB is huge with analysis. I mean, hands down. But across the board, if you can provide a few examples. Because there's so many teams in front offices putting such an, just a heavy intensity on the analysis side. And where the teams are going. And if you could provide any specific examples of teams that have really blown your mind. Especially over the last year or two. Because every year it gets more exciting if you will. I mean, so a big thing in baseball is defensive shifts. So if you watch tonight, you'll probably see a couple of plays where if you're used to watching baseball, a guy makes really solid contact. And there's a fielder there that you don't think should be there. But that's really very data driven where you analyze where's this guy hit the ball. That part's not so hard. But also there's game theory involved. Because you have to adjust for the fact that he knows where you're positioning the defenders. He's trying therefore to make adjustments to his own swing and so that's been a major innovation in how baseball is played. You know, how bullpens are used too. Where teams have realized that actually having a guy, across all sports pretty much, realizing the importance of rest. And of fatigue. And that you can be the best pitcher in the world, but guess what? After four or five innings, you're probably not as good as a guy who has a fresh arm necessarily. So I mean, it really is like, these are not subtle things anymore. It's not just oh, on base percentage is valuable. It really effects kind of every strategic decision in baseball. The NBA, if you watch an NBA game tonight, see how many three point shots are taken. That's in part because of data. And teams realizing hey, three points is worth more than two, once you're more than about five feet from the basket, the shooting percentage gets really flat. And so it's revolutionary, right? Like teams that will shoot almost half their shots from the three point range nowadays. Larry Bird, who wound up being one of the greatest three point shooters of all time, took only eight three pointers his first year in the NBA. It's quite noticeable if you watch baseball or basketball in particular. >> Not to focus too much on sports. One final question. In terms of Major League Soccer, and now in NFL, we're having the analysis and having wearables where it can now showcase if they wanted to on screen, heart rate and breathing and how much exertion. How much data is too much data? And when does it ruin the sport? >> So, I don't think, I mean, again, it goes sport by sport a little bit. I think in basketball you actually have a more exciting game. I think the game is more open now. You have more three pointers. You have guys getting higher assist totals. But you know, I don't know. I'm not one of those people who thinks look, if you love baseball or basketball, and you go in to work for the Astros, the Yankees or the Knicks, they probably need some help, right? You really have to be passionate about that sport. Because it's all based on what questions am I asking? As I'm a fan or I guess an employee of the team. Or a player watching the game. And there isn't really any substitute I don't think for the insight and intuition that a curious human has to kind of ask the right questions. So we can talk at great length about what tools do you then apply when you have those questions, but that still comes from people. I don't think machine learning could help with what questions do I want to ask of the data. It might help you get the answers. >> If you have a mid-fielder in a soccer game though, not exerting, only 80%, and you're seeing that on a screen as a fan, and you're saying could that person get fired at the end of the day? One day, with the data? >> So we found that actually some in soccer in particular, some of the better players are actually more still. So Leo Messi, maybe the best player in the world, doesn't move as much as other soccer players do. And the reason being that A) he kind of knows how to position himself in the first place. B) he realizes that you make a run, and you're out of position. That's quite fatiguing. And particularly soccer, like basketball, is a sport where it's incredibly fatiguing. And so, sometimes the guys who conserve their energy, that kind of old school mentality, you have to hustle at every moment. That is not helpful to the team if you're hustling on an irrelevant play. And therefore, on a critical play, can't get back on defense, for example. >> Sports, but also data is moving exponentially as we're just speaking about today. Tech, healthcare, every different industry. Is there any particular that's a favorite of yours to cover? And I imagine they're all different as well. >> I mean, I do like sports. We cover a lot of politics too. Which is different. I mean in politics I think people aren't intuitively as data driven as they might be in sports for example. It's impressive to follow the breakthroughs in artificial intelligence. It started out just as kind of playing games and playing chess and poker and Go and things like that. But you really have seen a lot of breakthroughs in the last couple of years. But yeah, it's kind of infused into everything really. >> You're known for your work in politics though. Especially presidential campaigns. >> Yeah. >> This year, in particular. Was it insanely challenging? What was the most notable thing that came out of any of your predictions? >> I mean, in some ways, looking at the polling was the easiest lens to look at it. So I think there's kind of a myth that last year's result was a big shock and it wasn't really. If you did the modeling in the right way, then you realized that number one, polls have a margin of error. And so when a candidate has a three point lead, that's not particularly safe. Number two, the outcome between different states is correlated. Meaning that it's not that much of a surprise that Clinton lost Wisconsin and Michigan and Pennsylvania and Ohio. You know I'm from Michigan. Have friends from all those states. Kind of the same types of people in those states. Those outcomes are all correlated. So what people thought was a big upset for the polls I think was an example of how data science done carefully and correctly where you understand probabilities, understand correlations. Our model gave Trump a 30% chance of winning. Others models gave him a 1% chance. And so that was interesting in that it showed that number one, that modeling strategies and skill do matter quite a lot. When you have someone saying 30% versus 1%. I mean, that's a very very big spread. And number two, that these aren't like solved problems necessarily. Although again, the problem with elections is that you only have one election every four years. So I can be very confident that I have a better model. Even one year of data doesn't really prove very much. Even five or 10 years doesn't really prove very much. And so, being aware of the limitations to some extent intrinsically in elections when you only get one kind of new training example every four years, there's not really any way around that. There are ways to be more robust to sparce data environments. But if you're identifying different types of business problems to solve, figuring out what's a solvable problem where I can add value with data science is a really key part of what you're doing. >> You're such a leader in this space. In data and analysis. It would be interesting to kind of peek back the curtain, understand how you operate but also how large is your team? How you're putting together information. How quickly you're putting it out. Cause I think in this right now world where everybody wants things instantly-- >> Yeah. >> There's also, you want to be first too in the world of journalism. But you don't want to be inaccurate because that's your credibility. >> We talked about this before, right? I think on average, speed is a little bit overrated in journalism. >> [Katie] I think it's a big problem in journalism. >> Yeah. >> Especially in the tech world. You have to be first. You have to be first. And it's just pumping out, pumping out. And there's got to be more time spent on stories if I can speak subjectively. >> Yeah, for sure. But at the same time, we are reacting to the news. And so we have people that come in, we hire most of our people actually from journalism. >> [Katie] How many people do you have on your team? >> About 35. But, if you get someone who comes in from an academic track for example, they might be surprised at how fast journalism is. That even though we might be slower than the average website, the fact that there's a tragic event in New York, are there things we have to say about that? A candidate drops out of the presidential race, are things we have to say about that. In periods ranging from minutes to days as opposed to kind of weeks to months to years in the academic world. The corporate world moves faster. What is a little different about journalism is that you are expected to have more precision where people notice when you make a mistake. In corporations, you have maybe less transparency. If you make 10 investments and seven of them turn out well, then you'll get a lot of profit from that, right? In journalism, it's a little different. If you make kind of seven predictions or say seven things, and seven of them are very accurate and three of them aren't, you'll still get criticized a lot for the three. Just because that's kind of the way that journalism is. And so the kind of combination of needing, not having that much tolerance for mistakes, but also needing to be fast. That is tricky. And I criticize other journalists sometimes including for not being data driven enough, but the best excuse any journalist has, this is happening really fast and it's my job to kind of figure out in real time what's going on and provide useful information to the readers. And that's really difficult. Especially in a world where literally, I'll probably get off the stage and check my phone and who knows what President Trump will have tweeted or what things will have happened. But it really is a kind of 24/7. >> Well because it's 24/7 with FiveThirtyEight, one of the most well known sites for data, are you feeling micromanagey on your people? Because you do have to hit this balance. You can't have something come out four or five days later. >> Yeah, I'm not -- >> Are you overseeing everything? >> I'm not by nature a micromanager. And so you try to hire well. You try and let people make mistakes. And the flip side of this is that if a news organization that never had any mistakes, never had any corrections, that's raw, right? You have to have some tolerance for error because you are trying to decide things in real time. And figure things out. I think transparency's a big part of that. Say here's what we think, and here's why we think it. If we have a model to say it's not just the final number, here's a lot of detail about how that's calculated. In some case we release the code and the raw data. Sometimes we don't because there's a proprietary advantage. But quite often we're saying we want you to trust us and it's so important that you trust us, here's the model. Go play around with it yourself. Here's the data. And that's also I think an important value. >> That speaks to open source. And your perspective on that in general. >> Yeah, I mean, look, I'm a big fan of open source. I worry that I think sometimes the trends are a little bit away from open source. But by the way, one thing that happens when you share your data or you share your thinking at least in lieu of the data, and you can definitely do both is that readers will catch embarrassing mistakes that you made. By the way, even having open sourceness within your team, I mean we have editors and copy editors who often save you from really embarrassing mistakes. And by the way, it's not necessarily people who have a training in data science. I would guess that of our 35 people, maybe only five to 10 have a kind of formal background in what you would call data science. >> [Katie] I think that speaks to the theme here. >> Yeah. >> [Katie] That everybody's kind of got to be data literate. >> But yeah, it is like you have a good intuition. You have a good BS detector basically. And you have a good intuition for hey, this looks a little bit out of line to me. And sometimes that can be based on domain knowledge, right? We have one of our copy editors, she's a big college football fan. And we had an algorithm we released that tries to predict what the human being selection committee will do, and she was like, why is LSU rated so high? Cause I know that LSU sucks this year. And we looked at it, and she was right. There was a bug where it had forgotten to account for their last game where they lost to Troy or something and so -- >> That also speaks to the human element as well. >> It does. In general as a rule, if you're designing a kind of regression based model, it's different in machine learning where you have more, when you kind of build in the tolerance for error. But if you're trying to do something more precise, then so much of it is just debugging. It's saying that looks wrong to me. And I'm going to investigate that. And sometimes it's not wrong. Sometimes your model actually has an insight that you didn't have yourself. But fairly often, it is. And I think kind of what you learn is like, hey if there's something that bothers me, I want to go investigate that now and debug that now. Because the last thing you want is where all of a sudden, the answer you're putting out there in the world hinges on a mistake that you made. Cause you never know if you have so to speak, 1,000 lines of code and they all perform something differently. You never know when you get in a weird edge case where this one decision you made winds up being the difference between your having a good forecast and a bad one. In a defensible position and a indefensible one. So we definitely are quite diligent and careful. But it's also kind of knowing like, hey, where is an approximation good enough and where do I need more precision? Cause you could also drive yourself crazy in the other direction where you know, it doesn't matter if the answer is 91.2 versus 90. And so you can kind of go 91.2, three, four and it's like kind of A) false precision and B) not a good use of your time. So that's where I do still spend a lot of time is thinking about which problems are "solvable" or approachable with data and which ones aren't. And when they're not by the way, you're still allowed to report on them. We are a news organization so we do traditional reporting as well. And then kind of figuring out when do you need precision versus when is being pointed in the right direction good enough? >> I would love to get inside your brain and see how you operate on just like an everyday walking to Walgreens movement. It's like oh, if I cross the street in .2-- >> It's not, I mean-- >> Is it like maddening in there? >> No, not really. I mean, I'm like-- >> This is an honest question. >> If I'm looking for airfares, I'm a little more careful. But no, part of it's like you don't want to waste time on unimportant decisions, right? I will sometimes, if I can't decide what to eat at a restaurant, I'll flip a coin. If the chicken and the pasta both sound really good-- >> That's not high tech Nate. We want better. >> But that's the point, right? It's like both the chicken and the pasta are going to be really darn good, right? So I'm not going to waste my time trying to figure it out. I'm just going to have an arbitrary way to decide. >> Serious and business, how organizations in the last three to five years have just evolved with this data boom. How are you seeing it as from a consultant point of view? Do you think it's an exciting time? Do you think it's a you must act now time? >> I mean, we do know that you definitely see a lot of talent among the younger generation now. That so FiveThirtyEight has been at ESPN for four years now. And man, the quality of the interns we get has improved so much in four years. The quality of the kind of young hires that we make straight out of college has improved so much in four years. So you definitely do see a younger generation for which this is just part of their bloodstream and part of their DNA. And also, particular fields that we're interested in. So we're interested in people who have both a data and a journalism background. We're interested in people who have a visualization and a coding background. A lot of what we do is very much interactive graphics and so forth. And so we do see those skill sets coming into play a lot more. And so the kind of shortage of talent that had I think frankly been a problem for a long time, I'm optimistic based on the young people in our office, it's a little anecdotal but you can tell that there are so many more programs that are kind of teaching students the right set of skills that maybe weren't taught as much a few years ago. >> But when you're seeing these big organizations, ESPN as perfect example, moving more towards data and analytics than ever before. >> Yeah. >> You would say that's obviously true. >> Oh for sure. >> If you're not moving that direction, you're going to fall behind quickly. >> Yeah and the thing is, if you read my book or I guess people have a copy of the book. In some ways it's saying hey, there are lot of ways to screw up when you're using data. And we've built bad models. We've had models that were bad and got good results. Good models that got bad results and everything else. But the point is that the reason to be out in front of the problem is so you give yourself more runway to make errors and mistakes. And to learn kind of what works and what doesn't and which people to put on the problem. I sometimes do worry that a company says oh we need data. And everyone kind of agrees on that now. We need data science. Then they have some big test case. And they have a failure. And they maybe have a failure because they didn't know really how to use it well enough. But learning from that and iterating on that. And so by the time that you're on the third generation of kind of a problem that you're trying to solve, and you're watching everyone else make the mistake that you made five years ago, I mean, that's really powerful. But that doesn't mean that getting invested in it now, getting invested both in technology and the human capital side is important. >> Final question for you as we run out of time. 2018 beyond, what is your biggest project in terms of data gathering that you're working on? >> There's a midterm election coming up. That's a big thing for us. We're also doing a lot of work with NBA data. So for four years now, the NBA has been collecting player tracking data. So they have 3D cameras in every arena. So they can actually kind of quantify for example how fast a fast break is, for example. Or literally where a player is and where the ball is. For every NBA game now for the past four or five years. And there hasn't really been an overall metric of player value that's taken advantage of that. The teams do it. But in the NBA, the teams are a little bit ahead of journalists and analysts. So we're trying to have a really truly next generation stat. It's a lot of data. Sometimes I now more oversee things than I once did myself. And so you're parsing through many, many, many lines of code. But yeah, so we hope to have that out at some point in the next few months. >> Anything you've personally been passionate about that you've wanted to work on and kind of solve? >> I mean, the NBA thing, I am a pretty big basketball fan. >> You can do better than that. Come on, I want something real personal that you're like I got to crunch the numbers. >> You know, we tried to figure out where the best burrito in America was a few years ago. >> I'm going to end it there. >> Okay. >> Nate, thank you so much for joining us. It's been an absolute pleasure. Thank you. >> Cool, thank you. >> I thought we were going to chat World Series, you know. Burritos, important. I want to thank everybody here in our audience. Let's give him a big round of applause. >> [Nate] Thank you everyone. >> Perfect way to end the day. And for a replay of today's program, just head on over to ibm.com/dsforall. I'm Katie Linendoll. And this has been Data Science for All: It's a Whole New Game. Test one, two. One, two, three. Hi guys, I just want to quickly let you know as you're exiting. A few heads up. Downstairs right now there's going to be a meet and greet with Nate. And we're going to be doing that with clients and customers who are interested. So I would recommend before the game starts, and you lose Nate, head on downstairs. And also the gallery is open until eight p.m. with demos and activations. And tomorrow, make sure to come back too. Because we have exciting stuff. I'll be joining you as your host. And we're kicking off at nine a.m. So bye everybody, thank you so much. >> [Announcer] Ladies and gentlemen, thank you for attending this evening's webcast. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your name badge at the registration desk. Thank you. Also, please note there are two exits on the back of the room on either side of the room. Have a good evening. Ladies and gentlemen, the meet and greet will be on stage. Thank you.

Published Date : Nov 1 2017

SUMMARY :

Today the ability to extract value from data is becoming a shared mission. And for all of you during the program, I want to remind you to join that conversation on And when you and I chatted about it. And the scale and complexity of the data that organizations are having to deal with has It's challenging in the world of unmanageable. And they have to find a way. AI. And it's incredible that this buzz word is happening. And to get to an AI future, you have to lay a data foundation today. And four is you got to expand job roles in the organization. First pillar in this you just discussed. And now you get to where we are today. And if you don't have a strategy for how you acquire that and manage it, you're not going And the way I think about that is it's really about moving from static data repositories And we continue with the architecture. So you need a way to federate data across different environments. So we've laid out what you need for driving automation. And so when you think about the real use cases that are driving return on investment today, Let's go ahead and come back to something that you mentioned earlier because it's fascinating And so the new job roles is about how does everybody have data first in their mind? Everybody in the company has to be data literate. So overall, group effort, has to be a common goal, and we all need to be data literate But at the end of the day, it's kind of not an easy task. It's not easy but it's maybe not as big of a shift as you would think. It's interesting to hear you say essentially you need to train everyone though across the And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. And I've heard that the placement behind those jobs, people graduating with the MS is high. Let me get back to something else you touched on earlier because you mentioned that a number They produce a lot of the shows that I'm sure you watch Katie. And this is a good example. So they have to optimize every aspect of their business from marketing campaigns to promotions And so, as we talk to clients we think about how do you start down this path now, even It's analytics first to the data, not the other way around. We as a practice, we say you want to bring data to where the data sits. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. Female preferred, on the cover of Vogue. And how does it change everything? And while it's important to recognize this critical skill set, you can't just limit it And we call it clickers and coders. [Katie] I like that. And there's not a lot of things available today that do that. Because I hear you talking about the data scientists role and how it's critical to success, And my view is if you have the right platform, it enables the organization to collaborate. And every organization needs to think about what are the skills that are critical? Use this as your chance to reinvent IT. And I can tell you even personally being effected by how important the analysis is in working And think about if you don't do something. And now we're going to get to the fun hands on part of our story. And then how do you move analytics closer to your data? And in here I can see that JP Morgan is calling for a US dollar rebound in the second half But then where it gets interesting is you go to the bottom. data, his stock portfolios, and browsing behavior to build a model which can predict his affinity And so, as a financial adviser, you look at this and you say, all right, we know he loves And I want to do that by picking a auto stock which has got negative correlation with Ferrari. Cause you start clicking that and immediately we're getting instant answers of what's happening. And what I see here instantly is that Honda has got a negative correlation with Ferrari, As a financial adviser, you wouldn't think about federating data, machine learning, pretty And drive the machine learning into the appliance. And even score hundreds of customers for their affinities on a daily basis. And then you see when you deploy analytics next to your data, even a financial adviser, And as a data science leader or data scientist, you have a lot of the same concerns. But you guys each have so many unique roles in your business life. And just by looking at the demand of companies that wants us to help them go through this And I think the whole ROI of data is that you can now understand people's relationships Well you can have all the data in the world, and I think it speaks to, if you're not doing And I think that that's one of the things that customers are coming to us for, right? And Nir, this is something you work with a lot. And the companies that are not like that. Tricia, companies have to deal with data behind the firewall and in the new multi cloud And so that's why I think it's really important to understand that when you implement big And how are the clients, how are the users actually interacting with the system? And right now the way I see teams being set up inside companies is that they're creating But in order to actually see all of the RY behind the data, you also have to have a creative That's one of the things that we see a lot. So a lot of the training we do is sort of data engineers. And I think that's a very strong point when it comes to the data analysis side. And that's where you need the human element to come back in and say okay, look, you're And the people who are really great at providing that human intelligence are social scientists. the talent piece is actually the most important crucial hard to get. It may be to take folks internally who have a lot of that domain knowledge that you have And from data scientist to machine learner. And what I explain to them is look, you're still making decisions in the same way. And I mean, just to give you an example, we are partnering with one of the major cloud And what you're talking about with culture is really where I think we're talking about And I think that communication between the technical stakeholders and management You guys made this way too easy. I want to leave you with an opportunity to, anything you want to add to this conversation? I think one thing to conclude is to say that companies that are not data driven is And thank you guys again for joining us. And we're going to turn our attention to how you can deliver on what they're talking about And finally how you could build models anywhere and employ them close to where your data is. And thanks to Siva for taking us through it. You got to break it down for me cause I think we zoom out and see the big picture. And we saw some new capabilities that help companies avoid lock-in, where you can import And as a data scientist, you stop feeling like you're falling behind. We met backstage. And I go to you to talk about sports because-- And what it brings. And the reason being that sports consists of problems that have rules. And I was going to save the baseball question for later. Probably one of the best of all time. FiveThirtyEight has the Dodgers with a 60% chance of winning. So you have two teams that are about equal. It's like the first World Series in I think 56 years or something where you have two 100 And that you can be the best pitcher in the world, but guess what? And when does it ruin the sport? So we can talk at great length about what tools do you then apply when you have those And the reason being that A) he kind of knows how to position himself in the first place. And I imagine they're all different as well. But you really have seen a lot of breakthroughs in the last couple of years. You're known for your work in politics though. What was the most notable thing that came out of any of your predictions? And so, being aware of the limitations to some extent intrinsically in elections when It would be interesting to kind of peek back the curtain, understand how you operate but But you don't want to be inaccurate because that's your credibility. I think on average, speed is a little bit overrated in journalism. And there's got to be more time spent on stories if I can speak subjectively. And so we have people that come in, we hire most of our people actually from journalism. And so the kind of combination of needing, not having that much tolerance for mistakes, Because you do have to hit this balance. And so you try to hire well. And your perspective on that in general. But by the way, one thing that happens when you share your data or you share your thinking And you have a good intuition for hey, this looks a little bit out of line to me. And I think kind of what you learn is like, hey if there's something that bothers me, It's like oh, if I cross the street in .2-- I mean, I'm like-- But no, part of it's like you don't want to waste time on unimportant decisions, right? We want better. It's like both the chicken and the pasta are going to be really darn good, right? Serious and business, how organizations in the last three to five years have just And man, the quality of the interns we get has improved so much in four years. But when you're seeing these big organizations, ESPN as perfect example, moving more towards But the point is that the reason to be out in front of the problem is so you give yourself Final question for you as we run out of time. And so you're parsing through many, many, many lines of code. You can do better than that. You know, we tried to figure out where the best burrito in America was a few years Nate, thank you so much for joining us. I thought we were going to chat World Series, you know. And also the gallery is open until eight p.m. with demos and activations. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your

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Tara Chklovski, Iridescent & Anar Simpson, Technovation | Part 2 | CUBE Conversation Aug 2017


 

(upbeat happy music) >> Hello, and welcome to a special CUBEConversations here at theCUBE Studio in Palo Alto. I'm John Furrier here for a special Women in Tech and Technovation conversation with Tara Chklovski founder and CEO of Iridescent also runs TechNation and Anar Simpson global ambassador of TechNation. Great Women in Tech conversation and you guys have done amazing work, you're both rock stars. Thanks for spending the time. We just had a great chat about your event you had the 2017 World Pitch competition for girls in entrepreneurship in coding and everything else. Congratulations, so tell us about Technovation. What do you guys do and you guys are doing some amazing work. Tara start us off, where are you guys and what's going on? >> So Technovation is the world's largest technology entrepreneurship program for girls and girls aged middle school and high school are challenged that you have to find a problem in your community, to learn how to code a mobile application and learn how to start a startup from scratch all the way to the pitch video business plan. And through that process they are partnered with a woman in tech mentor and they go through a hundred hour learning experience. At the end of it they have to submit their apps and business plans for judging, and we have thousands of judges who are experts in tech from all over the world, review those and then we have a quarter final, semi final and then the big World Pitch competition that was held last week here in Silicon Valley. >> And this sounds so progressive and cutting edge. It sounds like what Palo Alto high school would do with Menlo and Sacred Heart and Castilleja, but this is not just Silicon Valley this is, I mean talk to us a little bit about the scope of the program. How do people get involved? Share some of the data. >> Yeah, totally, and so it is all over the world. We run in a hundred different countries, primarily brought and expanded through our work that our global ambassador Anar has done, and most of it is really trying to bring girls who would have never been exposed to technology entrepreneurship careers. And the way we work is really through partnerships, amazing organizations and visionary leaders who do the hard work of actually supporting these girls, getting these girls interested. So these girls would typically never go into careers in tech because they never see themselves as being interested and so the hook is that you want to find a problem in your community. You have to go out, talk to people, try to understand what is a big problem that is worth solving, and then we say, "Oh by the way, you know you could solve "this problem using technology." And so you get in a whole another group of people that would not normally access these careers. >> So is it an application process? Is it in the US? >> Anybody can. >> So anyone in the US. >> Anybody. >> So my daughter who wants to get some community hours could actually go take it to a whole other level. >> Totally, so you can just register. We haven't launched the new season yet but it'll be out live in October. Sign up, find a team of girls, and there's actually a documentary, an award-winning documentary done about the program. So the same woman who did Inconvenient Truth wanted to profile Women in Tech and she did a whole documentary about Technovation and it's called CodeGirl and you can get it on any online video platform. >> That's awesome, well congratulations. It's super impressive work, very inspirational. And Anar, you're bringing the global perspective in and we were talking before we came on camera that you had a goal. Share with us your five year goal and an update of where you are in taking this out beyond the United States. >> Sure, so you know five years ago I was a mentor for Technovation. It was my first time and it was an amazing experience, and we won in the local competition and the regional competition and then placed third in the final competition. And after that I had a conversation with Tara about the amazing experience that I had, and we were chatting and she said she'd love to take this globally. And being the type A enthusiast that I am, I said oh, well okay that's fine, you know, I come from Kenya. I've lived in Canada, so we've got three-- >> John: The perfect mix. >> Yeah, three countries already, but I'm sure we can take it global. Well in fact with our work together, I was able to take Technovation to 18 countries in the first year, 34 countries in the second year, 72 countries in the third year and this year we're at over a hundred countries. And it hasn't been an easy road. We keep saying this to each other, we just keep trying. Our focus is on getting this program. We don't get caught into anything politics or any otherwise, and we just want to get to as many girls as we can. And as Tara said, partnerships have played an immense role in getting Technovation all over the world. So initially it was just cold calls, people I knew in Kenya, people I knew in Canada, people I knew in LinkedIn, my little circle. But then my circle got bigger and bigger and then lots and lots of opportunities presented themselves and one of them was the Tech Women program that's run by the State Department. They bring in senior technical women to Silicon Valley for an internship and then I said to them, Oh and when they go back home, what do they do? Shouldn't they do Technovation? And so we've done good partnerships with them, we've done a good partnership with the UN women. We've been profiled in the United Nations high-level panel report, and these things keep happening and the... But it's not just because of the community or the relationships we're building. Our program works. It is credible. Our impact reports show that these girls end up in tech-related fields as they progress, and that's the whole point of our purpose, right? Is to say look, girls everywhere should be entering technology fields and what Technovation does it it's building a pipeline of young girls to enter these careers all over the globe. >> Well it's no secret that the folks that know me and watch theCUBE and know the show know that I'm a huge proponent for computer science and you know it's kind of similar, we kind of fell into that in the '80s. It's now become very interesting in that the surface area for computer science has increased a lot, and it's not just coding heads down and squashing bugs and writing code. There's been a whole nother evolution of soft skills, Agile, Cloud, you're seeing a full transformation with the potential unlimited compute available. With mobile now 10 years plus into the iPhone, you see new infrastructure developing. So it creates the notion that okay, you can bring the science of computers to a whole nother level. That must be attractive as you guys have that capability to bring that to bear in the programs. Can you guys comment on how you guys see just the role of computer science playing out? This is not a gender thing, just more of, as I have a young daughter I try to say it's not just writing code you can certainly whip out a mobile app but it's really bringing design to it or bringing a personal passion that you might have. So what are some of the patterns you're seeing in this surface area of what's now known as computer science? >> I think it's super important because as technology has progressed we've been able to provide this program. If we were still programming with you know, the in front of screens and doing the what you see is what you get kind of thing without, we would not be there. I think the big thing that's happened in the last 10 years is the mobile phone. I mean if you find a girl anywhere today in the world, chances are she'll have a mobile phone on her and she's going to be loathe for you to take that one thing from her. You could take other things from her, but try taking that phone away from her, she will not let you. And so the fact that she's so attached to that mobile phone means that you can then tell her, hey you don't have to be just a consumer of that thing. You can be a producer of that thing. Anything that you see on there, you can actually design. This is power. This is your thing to good and great and better, and if we can shift that in their minds that this is their link to the world that's wide open, we're seeing that. >> Well the world in consumed by it, I mean a lot of women in the world will be consumers of product. Certainly with AI, the conversation over the weekend I was having with folks is the role of women. It's super important not just in AI, but as software becomes cognitive, you have to align with half the audience that's out there. So it'd be hard for a guy to program something that's going to be more oriented towards a woman. But it brings up the question of application, and whether it's self-driving cars or utility from work to play and everything in between. Software, and the role of software's going to be critical and that seems to be pretty clear. The question is how do you inspire young girls? That's the question that a lot of fellow males that I talk to who are fathers of daughters and or are promoting Women in Tech and see that vision, what are some of the inspiration areas? How do you really shake the interest and how do you have someone really kind of dig in and enjoy it and taste it and feel it? >> Right, right. >> So there is some research to back what the formula is that works and to drive change in behavior. And so there is this, one of the biggest sort of names in cognitive psychology is Albert Bandura. He's a professor at Stanford. But basically it's the same principles that drives say the addiction from alcohol or weight loss or any kind of new behavior change. So the first is you need to have exposure to someone who you respect showing that this is something of meaning. So the key words are someone you respect, right? And so media can play a very big role here for scale, right otherwise it's only maybe your teacher or your parent and if they're not exposed to technology, they can't really affect your, and so media can play a huge role there. Second is the experience itself, right. Like how do you make it easy to get started, and then it's like learning from video games, right. So you make it very very easy, like the first step is just come over here it'll be fun, there's pizza, come right, like your friends are coming. But then the feedback has to be very fast, so the first step and that's where a good curriculum matters, right. So that's where also working on a mobile phone is very appealing even though many apps is-- >> John: It's relatable. >> It's relatable but the feedback is instantaneous, and so the programming language that the girls use is block based so even though you don't have any prior programming background you can still build a working app so that's critical. Then human beings get tired very easily and so the feedback needs to keep changing. It has to be unpredictable. The third piece is that of expectations, and so you have to have very high expectations, and so that's why this current discussion around cognitive differences in gender I feel is missing the point because it's not what you're born with, what are you capable of? And so if we looked at our genetics we would never go to space, we would never go to the deepest parts of the ocean because we are not meant for that, right? But we had really high visions and expectations and so human beings rose to that. And then the last piece is less relevant in developed countries but it's still important so, it's sort of the human energy. We are not a brain dissociated from the body. We are connected, right, and so if you're hungry and tired and sleepy, not the right time to sort of make a dramatic change in your interests. So this is relevant, if for us, we try to figure out which countries are we going to work in, so post conflict, war torn areas are not the best areas to start a new program in. You need the right partners. >> So you're saying the biological argument of, of course they're different, men and women. >> Yes. >> But it's the capability, that's where people are missing the boat. >> And the support system, right? So have high expectations, provide them with the right support, but the most important thing is your own beliefs in that. >> Let's get your thoughts on that because I think you guys have a great program with Technovation. You mentioned mentors, key part of the formula most likely. What we hear in the conversations I've had with women peers has been you know, there's a real call to arms at the executive level now, folks my age in their fifties who made it who are there succeeding. They really want to give back and they really have recognized the value of having that peer mentorship and then inspiring the young generation. Whether it's part of the things we cover like Grace Hopper or Technovation things that you do. Or even just mentoring in their own communities. What does that mentorship look like that you guys see, that you'd like to see doubled down on or areas you'd like to see tweaked or perceptions that need to change. What's your thoughts on mentorship and the role of inspiring young girls? >> Mentorship from men? >> John: Men and women, I mean. >> From both. >> John: Well I see the mentoring with women, that's the first step. >> Right. >> I have a whole nother conversation in my opinion that the men need training. Not just like go to class and learn how to talk but how to empathize. >> Well my big thing has been that you know when you wanted to encourage women up the ladder in your companies or you want to encourage women to actually get in to technical roles. That intent should not be placed in the CSR department of your organization 'cause that speaks volumes, right. To say oh, well that's in the social responsibility department or the HR, that just says okay, so you're not really, you don't think we're capable of helping you with your product or service. We're sort of part of this and it's like, no, you know. So I think you want to mainstream it, which is what a lot of I and D things are trying to do now. >> John: Inclusion and diversity. >> Inclusion and diversity techs. >> To make it part of the fabric not a department checkbox. >> Exactly, and-- >> That's what you're getting at right? >> Exactly, and you know the evolvement of these departments to include everybody and to make it more diverse is going to be not frictionless, it will be friction until a time where it won't even be necessary. I and D departments should have one goal, which is to work themselves out of a job. If they can work themselves out of a job, then the company would have done what it needs to be done. But I think-- >> John: Meaning it's self sufficient, it's self governing. People are humans, there's respect for individuals. >> Yes. >> I mean this is basically comes down to if you look at it as humans it takes, every conversation could be tabled as, what? There's a person on the other side, it's a human being. Not a woman or a white male or whatever. >> And you know-- >> There's not there yet, but I mean certainly that would be the end game, so in that scenario that department's out of business the I and R, the inclusion and diversity department has done it's job. >> You don't need one, because exactly. You don't need one because you know, you're okay, and I think capabilities is really important. In corporations, and this isn't anybody's fault. This is just how it's been done. This has just been the culture of it, right? Who gets invited to which meetings? Who gets invited to which conferences, right? And so we heard the CEO of YouTube, Susan Wojcicki saying you know, she had to sort of elbow a little bit to say why am I not allowed at a certain conference? And it's like, maybe just wake up to that and say, well why aren't you involving more people at conferences and think tanks because you know, I come from a oil and gas background, and people used to do a lot of deals on the golf course because oil and gas people play golf a lot and a lot of deals used to happen. Well in the Valley we don't play golf a lot but we do do other things, conferences or get togethers and if you don't include the people in your team as groups or representationally well then they're not going to be there when you make these decisions. So maybe just be a little bit-- >> Exclusionary is a problem and Kleiner Perkins was taken to task. They had ski trips apparently planned and they didn't, well mostly guys and they didn't invite the woman partner. It was a big scandal. This is where they kind of make that, it's a normative thing they've got to change the norms. >> It's change the norms and if you actually want your company which is made of all kinds of people, to move really far ahead, don't be like that. Include everybody because the only goodness about that is you'll go forward. You don't include somebody, well you're going to hurt them and then they won't be able to contribute because they just can't and then your product or your service is going to fail. It's really simple. >> You mentioned the Susan Wojcicki post, was an article in Fortune magazine where she wrote a guest article and she mentioned her daughter. >> Yes. >> Was feeling the narrative which by the way changed from the original Google memo to have a different meaning, but that's what she heard. So the question to you guys that I have on that is with Technovation and the work that you're doing, you're exposed to a lot of the ecosystem, across the world not just in the US from young girls. >> Yes. >> They see what's coming down from the top or the media, so certainly it's the game of telephone as things translate down to the level of the girls. Is there a pattern that you see emerging in their eyes as they look at this nonsense of narratives that are moving around. It's kind of a moving train the narrative of gender, Women in Tech but ultimately they have to internalize it and what patterns do you see and what do you guys do to either nullify that misperception and how do you amplify the real perceptions? >> Can I take that one? I was in Nairobi at the Safaricom headquarters. I don't know if you know Safaricom but these are the people who came up with M-PESA, and this is the currency that you can do on your mobile phone and Kenya uses M-PESA, like almost everybody in Kenya uses M-PESA. So Safaricom is a big tel-co and it's a big deal in Kenya, and Safaricom has taken Technovation, it has embraced Technovation in a big way. And the people who embraced Technovation at Safaricom in a big way are both male. So Josephine who is a tech woman fellow who came here and then went back and started Technovation. Her director, Clibeau Royal, he's male and the CEO of Techno, CEO of Safaricom is Bob Collymore and he's also male and these men, if I could clone these men in every country with every company you would see this sort of moving away and shifting away that women aren't good engineers or can't be good engineers. They are embracing it in such a way, not because they like Technovation because they know for their business having more women and equal women and a diverse company is making their product and their goods better. >> John: Yeah, their arbitraging the labor pool, why would you ignore talent? >> Exactly. >> Whether they're over 50 or they're women, it doesn't matter. >> I want to add to that, so there's quite a bit of data, so the pattern's are not anything different from what the message girls get from school and parents, right. So if you look at the data, there are a hundred countries that legally discriminate against women. And so what industry, what message industry is telling is really firstly doesn't filter through to the larger population. Silicon Valley is a completely different bubble. But overall the message is girls are given is like, this is not for you, right, and so especially in some of the more sort of populous dense countries in the world. And so we have to fight a lot of these kinds of perceptions from the ground up, and the number one sort of gatekeeper is the father and so a key part of what we have now done to date is to provide sort of education and training to the parents because... There's a very moving story that, we work in a remote town in South India and a mentor who's very dedicated has been trying to get these girls to participate in Technovation. He did that and then there were, one girl was actually offered a job but the father kept sort of saying no, not needed, no girl in my family ever needs to work, but he fought it. And then so then the girl actually gets a job, and then a year later the father calls the mentor and said, "You know what, I'm so grateful that you did it "because a day after she got the job I got hit in "an accident and I lost my job." But it's these kind of perceptions that have to be changed one person at a time, which is what makes this very hard. Unless you actually are able to get the media to change sort of the messaging. And I think in the US which is, there is some very interesting studies on that question, right. If you were to think, would there be more women in STEM in poorer developing countries versus richer highly developed countries, where would you see more women in STEM? The answer is actually the women in poorer countries like Iran, Malaysia. The reason is because in an individualistic society like in the US where there's a lot of emphasis on materialistic but it's also about are you happy? The conversation has changed to, from parents telling children do what makes you happy, and then you're very prone to advertising, and advertising works when it's highly targeted and highly gendered. And so in the '60s there was no such thing as pink and blue, now there is pink and blue, right? And so now we have just made our entire society entirely susceptible to advertising, and girls are passive and compliant and boys are aggressive. And so then when you are looking at the board structures, there's no, it's very very hard to fix the problem right there, right? You have to go down deeper because you don't get leaders who are compliant, maybe secretaries are compliant. But you have to fix the message that teachers give girls, that parents give their baby girls when they're born. And so industry is just sort of in the spotlight right now, but the issue is not that of industry it's also that of society. >> Industry (mumbles) are supporting you guys is interesting that this industry seems to be chipping, and certainly Silicon Valley's a little bit different as you said, but in general it is a cultural parent thing. Any plans there with Technovation to have a parent track? (laughing) >> Yes totally, I mean I think right now 10% of parents actually volunteer to be mentors, kind of like say Girl Scout troop leaders and so we are trying to figure out okay what is a way to involve parents and to make them part of the discussion. >> Well we'll keep the conversations going with Technovation you guys do incredible work. I'll just end the segment here by just telling a little bit about what you're working on right now? What are your goals? What are you passionate about? What are some of the things you'd like to do in the next half of the year, next year? What are some of the things going, Tara, you start. >> I think for us is to go deeper, so we are just launching a partnership with MIT to increase sort of the rigor of the curriculum, the rigor of the training and also provide more personalized learning and so this is the power of technology so we don't want to have girls drop out of the program because it's a hard program. So really trying to bring the best from industry to support that. >> Right and so you know my goal is to get Technovation to all the countries in the world, but keeping in mind we're making sure that it's delivered in a really good way and so girls complete the program et cetera, and the model that I hope to replicate in many other countries is the model that we're trying within Canada. So the new Canadian government is very interested in making sure that all of its citizens are you know, innovative, ready for the technology change that's coming there, and they launched a new fund called CanCode and so we have been part of that application process and we hope to have Technovation in almost every city in Canada, across Canada, and to really get this going and we, right now Canada is, everybody's like, you know, favorite country. And we hope that if we can do this in Canada, then other countries will follow and so that this program will get to as many girls as it can. >> Well you know how I feel. I feel computer science training in general should be standard in curriculums, because of all the conversation around automation. Automation is the fear is that jobs will go away. The data we have from our research over at Wikibon shows that the billions being automated away is non-differentiated labor. >> Right. >> Which implies that a working knowledge of those machines will shift to the value side. So you know I'm on the pro side of AI and automation personally. Especially I think it's great for-- >> But there's an education side too. >> There's the education side and I think this is a real fun area. You guys are at the cutting edge of it, both doing great work. I appreciate you taking the time and we'll have you back in for an update. Tara, Inar thanks so much. This is theCUBE Conversation here in Palo Alto I'm John Furrier thanks for watching. (upbeat happy music)

Published Date : Aug 15 2017

SUMMARY :

Great Women in Tech conversation and you guys At the end of it they have to submit their apps about the scope of the program. and so the hook is that you want to find could actually go take it to a whole other level. and you can get it on any online video platform. that you had a goal. And being the type A enthusiast that I am, and that's the whole point of our purpose, right? So it creates the notion that okay, you can bring And so the fact that she's so attached to that mobile phone Software, and the role of software's going to be critical So the first is you need to have exposure to someone and so the feedback needs to keep changing. So you're saying the biological argument of, But it's the capability, that's where people And the support system, right? Whether it's part of the things we cover like John: Well I see the mentoring with women, that the men need training. So I think you want to mainstream it, Exactly, and you know the evolvement of these departments John: Meaning it's self sufficient, it's self governing. There's a person on the other side, it's a human being. that department's out of business the I and R, and if you don't include the people in your team it's a normative thing they've got to change the norms. It's change the norms and if you actually want You mentioned the Susan Wojcicki post, So the question to you guys that I have on that and what patterns do you see and what do you guys do and this is the currency that you can do it doesn't matter. And so in the '60s there was no such thing as pink and blue, is interesting that this industry seems to be chipping, and so we are trying to figure out okay what is a way What are some of the things going, Tara, you start. of the program because it's a hard program. Right and so you know my goal is to get Technovation Automation is the fear is that jobs will go away. So you know I'm on the pro side of AI and we'll have you back in for an update.

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Day 2 Keynote Analysis - SAP SAPPHIRE NOW - #SAPPHIRENOW #theCUBE


 

(lively music) >> Announcer: It's the CUBE, covering SAPPHIRE NOW 2017, brought to you by SAP cloud platform and HANA Enterprise Cloud. >> Welcome back, everybody. Jeff Frick here with the CUBE with our ongoing coverage of SAP SAPPHIRE 2017 down in Orlando. Really exciting day today, day two, 'cause we got to see Hasso Plattner. Got up and gave his keynote. Joined by George Gilbert. George, great to see you. I know you've known Hasso for years and years and years. Impressions of the kfeynote. God, there is so much stuff that we can dig into. I'm looking forward to it. >> Hasso almost never disappoints, 'cause he's just got %a richness of history and of vision that goes all the way back to the beginning. He was probably the technical visionary from the very beginning. He was the guy who took them from the first super integrated mainframe ERP package all the way to the client server age with R3, and now beyond into sort of in-memory, cloud ready, and with machine learning and iOT baked in. >> But he really speaks like a developer. You can really tell that he likes the technology, he understands the technology, he's kind of a no-BS guy. Some of the Q&A afterwards, people were trying to trip him up and challenge him on stuff. And he would either say, "I don't know," or, "I don't believe that," or, "Here's our impression." Really you could tell he's a humble guy, smart guy, and really has a grasp of what the heck is going on here. Let's jump into it. So many themes we could talk about. But the one that started out early in the conversation was, he literally said, "We need to get as quickly "to the cloud as possible." This is coming from a guy who built the company based on on prem ERP heavy lifting. And even he said today, 2017, "We need to get to the cloud as quickly as possible." >> I think there are a few things going on behind there, when you unpack it. One is, they did start building for the cloud in the early 2000's. It was meant to be a product for the mid-market. In fact, actually its first objective wasn't to be cloud-ready. The first objective was to be highly configurable so that you could bend it to the needs of many customers without customizing it, because typically with the customizations, it made it very difficult to upgrade. In making it configurable first and cloud-read second, they kind of accomplished neither. But they learned a lot. So they started on this next version, which was, okay, we're going to take an in-memory database which we're building from the ground up, 'cause Oracle wasn't building it at the time, and then we're going to build SAP ERP from scratch on top of this new database, 'cause database was so high performance that they didn't have to sepyarate analytics from transactions the way traditionally you do, you had to do in all applications. So they could simplify the app. Then, in simplifying it, they could make it easier to run in the cloud. And now, just like Oracle, just like Microsoft, they now build cloud first and on-prem second, because by building it cloud first, it sort of simplifies the assumptions that you have to make. >> Right, and he talked quite a bit about so much effort now is around integration connectors, to get stuff in and out of this thing. And that's a big focus, he said. It's not that we're ignoring it, it's just a big, hard, hairy problem that we're attacking. >> Yeah, and this is interesting and there's a lot of history behind this. Oracle, in the 90s, up until about the late 90s, their greatest success was in their industry-specific applications, where they took different modules from different vendors and stitched them together. That was how they built, like, a special solution for a consumer package goods company. But it turned out that that wasn't really workable because the different modules for the different vendors6 upgraded at different rates. So there was no way coherently to integrate them and tie them together. And SAP had said that all along. They were, like, this wasn't going to work. Fast forward to the last five-plus years, SAP started buying products from a bunch of different vendors, Ariba, SuccessFactors, Concur, Hybris. So you're, like, "Aren't they doing the same thing "Oracle did 10 year, 15 years before?" But no, and this is what Hasso was talking about today, which was, once those apps are in the cloud, you only have to build the integration points once. It's not like when it's on every customer's data center, you have to build integrations that work for every version that every customer has. So I think that's what he was talking about. You put it all in the cloud, you integrate it once. >> Another thing that he talked, he really, he spoke in tweets. (mumbles) goes to buy Twitter feed, I was basically, like, bang, bang, bang as he was talking. He talked about databases, and databases in the cloud. Nobody cares, right? It's a classic theme we hear over and over. "We presume it works. "We just want it to work." You know, it should just work. Nobody really cares what the underlying database is. >> But he was, in those cases, referring to these purchased apps, Concur, SuccessFactors, Ariba, Hybris. He was, like, "Some of them work on SQLServer, "some of 'em work on Oracle. "But you know what? "Until we get around to upgrading them to HANA, "it doesn't matter because you, the customer, "don't know that." If they were on prem and you had to support all those different databases, it might be a different story. But he's, like, "We'd rather give you the functionality "that's baked into them now "and get around to upgrading the databases later." >> Another thing that came up, and he actually reference the conversation with Michael Dell from yesterday's keynote, about the evolution of compute horsepower. You know, you had CPUs and CPUs kind of topped out. Then you had multicore CPUs. Now we have GPUs that he said you can put 10s or 100s of 1,000s on the board at one time. Basically he's smart guy, he's down the road a few steps from delivering today's product, saying that, you know, we're basically living in a era of unlimited free compute and kind of asymptotically approaching. But that's where we are. And how does that really change the way that we look now at new application development. I thought that was a pretty interesting thing. >> And sort of big advances in software architecture come from when you have a big change in the relative cost of compute memory, network storage. So as you were saying, cost of compute is approaching zero. But the same time, the cost of memory relative to storage is coming way down. So not only do you have these really beefy clusters with lots of compute, but you also have lots of memory. He was talking about something like putting 16 terabytes of memory in a server and putting 64 servers in a cluster, and all of a sudden, I can't do that math, being that I was a humanities major, but all of a sudden, you're talking about huge databases where you can crunch through this stuff very, very fast because it's all, you have lots of processors running in parallel and you have lots of memory. >> It's pretty interesting. He made an interesting statement. He used a sailor reference. He said, "You know, we are through the big waves "and now we're in the smooth water," and really saying that all this heavy lifting and now that this cloud architecture is here and we have this phenomenal compute and store technology, that he can kind of take a breath and really refresh a look out into the future as to, how do we build modern apps that have intelligence with basically unlimited resources, and how does that change the way that we go forward? I thought that was an interesting point of view, especially 'cause he has been at it for decades. >> You know, I think he was probably looking back to some of the arrows he had in his back from having done an in-memory database essentially before anyone else did for mission critical apps. I think when he's saying we're out of the choppy water and into the smooth water, because we now have the hardware that lets us run essentially these very resource-intensive databases and the apps on 'em, so that we no longer have to worry, are we overtaxing the infrastructure? Is it too expensive to outfit the hardware for a customer? So his, when he talks about rethinking the apps, he, like, "We don't have to have separate analytical systems "from the transaction systems. "And not only that. "We can simplify because we don't have to have" what he's calling aggregates. In other words, we don't have to, we don't, let's say, take an order and all the line items in an order, and then pre-aggregate all the orders. It's, like, we do that on the fly. And that simplifies things a lot. Then, not only that. Because we have all this memory, we can do, like, machine learning very inexpensively. >> A whole another chapter in his keynote was about modern software design. A lot of really interesting things, especially in the context of SAP, which was a big, monolithic application, hard to learn, hard to understand, hard to manage. I remember a start, that were were (mumbles) using is a core V to C commerce engine. And to add 16 colors of shirts times 10 neck sizes and 10 sleeve sizes was just a nightmare. You're not going to have some merchant that works at Macy's to put that into the system. But he talked about intelligent design, which is pretty interesting. We're hearing that more and more in a lot of work done over at Stanford, intelligent design. He's talking about no manuals. He's, like, "If I can't figure it out, "I need to understand." He talked about intelligent applications that continue to learn as the applications get more data. And specifically, the fact that machines don't get bored testing 100s or 1,000s or even millions of scenarios and grinding through those things to get the intelligence to start to learn about what's going on. So a very different kind of an application, both development, delivery approach, than what we think of historically as R3. >> Yeah, like the design thinking was, they have this new UI called Fiori. I mean, if you go back 10, 15 years, let's say, when they started, 15 years, when they started trying to put browser-based user interfaces on what was a client server system, they had 10s and 10s of 1,000s of forms-based screens. They had to convert them one by one to work in a browser. I think what he's saying now is, they can mock up these prototypes in a simple tool and they can essentially recreate the UI. It's not going to be the exact same forms, but they can recreate the UI to the entire system so that it's much more accessible. On the machine learning front, he was talking about one example was, like, matching up invoices that you going to have to pay. So that you going to train the system with all these invoices. It learns how to essentially do the OCR, recognize the text. And it gets smarter to the point where it can do 95% of it without-- >> Human interaction. >> Yeah, human inter-. >> You know, it's interesting, we were at Service Now last week, as well. And they are using AI to do relatively mundane tasks that people don't want to do, that machines are good at, things like categorization and assignment and things that are relatively straightforward processes but very time-consuming and again, if you can get to a 70% solution, 80% solution, 90% solution, to free people up to do other things on the stuff that's relatively routine. Right, if the invoice matches the anticipated bill in the system, pay it. Does somebody really have to look at it? So I thought that was really interesting. Something I want to dig in with you, he talked a lot about data, where the data lives, data gravity. He even said that he fought against data warehousing in the 90s and lost. A lot of real passionate conversation about where is data and how should apps interact with data, and he's really against this data replication and a data lake and moving this stuff all around, but having it kind of central. Want to just get your thoughts on that history. What do you think he means now, and where's that going? >> It's a great question. There's a lot of history behind that. Not everyone would remember, but there was an article in Fortune Magazine in the late 90s, where it described him getting up in a small conference of software CEOs, enterprise software CEOs, and he said basically, "We're going to grind you into dust, "because everything comes in our system integrated. "And if you leave it up to the customer "to try and stitch all this stuff together, "it's going to be a nightmare." And that was back when everyone was thinking, "One company can't do it all." And the reality was, that was the point in time where we really had given go past go, collect $200, to every best-of-breed little software vendor. It did prove out over the next decade that the fewer integration points there were, that it meant much lower cost of ownership for the customer. Not only lower cost of ownership, but better business process integration, 'cause you had the (mumbles) integration. I bring this up because, well, actually, I was there when he said it. (laughs) But I bring it up because he's essentially saying the same thing now, which is, "We'll put all the machine learning technology, "the building blocks, in SAP. "If you need any contextual data, "bring it into our system. "You don't want to take our data out "and put it into all these other machine learning programs "'cause there's security issues, "there's, again, the breakdown "in the business process integration." He did acknowledge that with data warehouses, if you have 100s of other sources, yes, you may need a external data warehouse. But I think that he's going to find with machine learning the greatest value with the data that you use in machine learning is when you're always adding richer and richer contextual data. That contextual data means you're getting it from other sources. I don't think he's going to win this battle in terms of keeping most of it within SAP. >> It kind of bring up this other intersection that he talked about. In now delivering SAP as a cloud application, he said, "Now we have to learn how to run our application, "not our customers," a very different way of looking at the world. The other thing that piggybacks off of what you just said is, we've seen this trend towards configuration, not customization. It used to be probably, back in the days, if you had the big SI's, they loved customization, 'cause it's a huge project, multi-years. I used to talk to one of our center partners, like, "How do you manage a multi-year SAP project "when most the people that started it "probably aren't even there the day you finish it?" But he had a specific quote I wanted to call out now, what you just said, is that he said, "Only our customers have the data, "the desire, and the domain knowledge "to make the most out of it." So it's a really interesting recognition that yes, you want customers to have this configuration option. But we keep hearing more and more, it's config, not-- >> Both: Customization. >> For upgrades and all these other things, which now when you go to a cloud-based application, that becomes significant. You don't want customizations, 'cause that's just complicates everything. >> You can't. I don't know if he said this today. I guess he must have said it today. But basically, when you're in the cloud, I forgot the terminology for the different instances. But when you're in, like, the SAP cloud, you can only configure. There's essentially a set of greater constraints on you. When you go to the other end of the spectrum, let's say you run it in your own data center, you can customize it. But when you're running it, essentially sharing the infrastructure, you're constrained. You're much more constrained. And they build it for that environment first. >> Right. But at the same time, they've got the data. Again, this has come up with other SAS companies that we've talked to, is hopefully, their out of the box business process covers 90% of the basics. I think there's been a realization on the business analyst side that we think we're special, but really most of the time, order to cash is order to cash. So if you got to tweak your own internal process to match best-of-breed, do it. You're much better off than trying to shape that computing system to fill your little corner cases. >> It's funny that you mention that, because what happened in the 90s was that by far the biggest influencers in the purchase decision and the overall lifecycle of the app were the big system integrators. They could typically collect $10 in implementation and change management fees for every dollar of license that went to the software vendors. So they had a huge incentive to tell the customer, "Well, you really should customize this "around your particular needs," because they made all the money off that. >> Right, right. Another huge theme. Again, it was such a great keynote. We watch a lot of keynotes, and I have a very high bar for what I consider a great keynote. This was a great keynote by a smart guy who knows his stuff and got history. But another theme was just really about AI. He talked a little bit, which I thought was great. Nobody talks about the fact that airplanes have been flying themselves for a very long time. So it is coming. I think he even said, maybe this is the age of AI. But there always have to be some humans involved. It's not a complete hand-over of control. But it is coming, and it's coming very, very quickly. >> I actually thought that they were a little further behind than might expected, considering that it's been years now that people in software have seen this coming. But they have in the dozens of applications or functions right now that are machine learning enabled. But if you look out at their roadmap, where they get to predictive accounting, customer behavior segmentation, profile completeness for in sales, solution recommenders, model training infrastructure for the base software foundation, they have a pretty rich roadmap. But I guess I would have thought it'd be a little farther along. But then Oracle isn't really any farther along. (mumbles) has done some work for HR. For whatever reason, I think that enterprise application vendors, I think they found this challenging for two reasons. On the technical side, machine learning is very different from the traditional analytics they did, which was really essentially OLAP, you know, business intelligence. This requires the data scientists and the white lab coats and instead of backward-looking business intelligence this forward-looking predictive analytics. The other thing is, I think you sell this stuff differently, which is, when it was business intelligence, you're basically selling reporting on what happened to department heads or function leaders, whereas when you're selling predictive capabilities, it's a little more transformative and you're not selling efficiency, which is what these applications have always, that's been their value preposition. You're selling transformational outcomes, which is a different sort of selling motion. >> It's funny, I heard a funny quote the other day. We used to look backwards for the sample of the data. (laughs thinly) Now we're in real time with-- >> Both: All the data. >> Very different situation-- >> And forward-looking. >> And forward-looking as well, with the predictive. >> That's a great quote, yeah. >> Again, he touched on so many things. But one of the things he brought up is Tesla. He actually said he has two Teslas, or he has a second Tesla. And there was question and answer afterwards really about the Tesla, not as the technology platform. And he poked fun at Germans. He said Germans have problems with simplicity. He referenced, I presume, a Mercedes or a Porsche, you know, the perfectly ergonomically placed buttons and switches. He goes, "You sit in a Tesla "and it just all comes up on the touch screen. "And if you want to do an update overnight, "they update your software, "and now you have the newer version of the car," versus the Mercedes, where it takes 'em three years to redesign the buttons and switches. I thought that was interesting. Then one of the Q&A people said, "But what about the buying experience? "If you (mumbles) ever bought a Tesla, "it's a very different experience "than buying a car." How does that really apply to selling software? It was pretty interesting. He said we're not there yet. But he has clearly grasped on, it's a new world and it's a new way to interact with the customers, kind of like his no manuals comment, that Tesla is defining a new way to buy a car, experience a car, upgrade a car. >> Operate it. >> At the same time, he got the crazy mode, fanatical mode, like, ludicrous mode, so that he could stop and tell the Porsche guys that you're falling behind further every single day. So I thought, really interesting, bringing that kind of consumer play and kind of a cutting edge automotive example into what was historically pretty stodgy enterprise software space. >> You know, it's funny, I listened when you're saying that. That was almost like the day one objective from SalesForce, which was, we want an enterprise app like Sebol, but we want an eBay-like, or Yahoo-like experience. And that did change the experience for buying it and for operating it. I think that was almost 20 years ago, where that was Marc Benioff's objective and he's saying it's easier to do that for CRM, but it's now time to bring that to ERP. >> The other thing he brought in which I was happy, being a Bay Area resident, is the Sharks. Because he's a part owner of San Josey Sharks, obviously it's SAP Center now, also known as the Shark Tank. It used to be owned by another technology company. But he made just a funny thing. "I like hockey, so I should like SAP," and he was talking about the analysis of how often the logos come up on the telecast et cetera. But the thing that struck me is, he said the analysis is actually now faster than the game. Pretty interesting way to think about this data in flow, in that the analysis coming out of the game that feeds Vegas, it feeds all these stat lines, it feeds fantasy, it feeds all this stuff, it feeds the advertising purchase and the ROI on my logo, is it in the corner, is it on the ice, is it in the middle, is actually moving faster than the hockey game. And hockey is a pretty fast game. Very different world in which we live, even on the mar-tech side. >> That was an example of one of the machine learning-type apps, because I think in their case, they were using, I think, Google image recognition technology to parse out essentially all the logos and see what type of impact your brand made relative to your purchase. >> I mean, I could go on and on. I've so many notes. Again, I live tweeted a lot of it, you know, he's just such a humble guy. He's a smart guy. He comes at it with a technology background, but he said we're a little bit slower than we'd like, he talked about some things taking longer than he thought they would. But he also now sees around the corner, that we are very quickly going to be in this age of infinite compute, and we are already in an age of, no one's reading manuals. Just seemed very kind of customer-centric, we're no longer the super-smart Germans that, "We'll do it our way or the highway, "and you will adapt your process to us," but really customer-centric point of view, design thinking, talked about sharing their roadmap as far out in advance as possible. I think he specifically, when he got questioned on design thinking, he's, like, "You know, the studies show that a collaborative effort "yields better results. "It's no longer, 'We're the smartest guy in the room "'and we're going to do it this way "'and you're going to adapt.'" So really progressive. >> And he talked about, with Concur, he said their UI is so easy that you really don't need a manual. In fact, if you do, you failed. And I think what he's trying to say is, we're going to take that iterative prototyping capability agile development and extend it to the rest of the ERP family. With their Fiori UI and the tools that build those screens that it'll make that possible. >> You've handled CAP. We don't spend enough investment on design in UI, 'cause it is such an important piece of the puzzle. But George, we're running out of time here. I want to give you the last word. You've been paying attention to SAP for a very long time. Hasso's terrific, but then Hasso gets off the stage and he said, "I don't run the company any more. "I only make recommendations." As you look at SAP, and Bill McDermott was yesterday, are they changing? Are they just stuck in an innovator's dilemma because they just make so much money on their historical business? Or are they really changing? What's your take as they develop, where they are now, and what do you see going forward for SAP? >> Well it's a really good question. I would say, I look at the value of the business processes that they are either augmenting or automating. I hesitate to say automate because, as he said, you still want the pilot in the cockpit. >> Jeff: In proximity to take control. >> Right. And he was, like, "Look, when we do the invoice matching, "it's not like we're going to get 100% right. "We're going to get it," I think he was saying, like, in the labs right now it's, like, 94% right. So we're going to make you more productive, we're not going to eliminate that job. But when you're doing invoice matching, that's not a super high value business process. If you're doing something where you're predicting churn and making a next best offer to a customer, that's a higher value process. Or if you have a multi-touchpoint commerce solution where you can track the customer, whether it's mobile, whether he's coming via chat, whether he's in the store, and you're able to see his history or her history and what's most appropriate given their context at any one moment, that's higher value. And then it's super high value to be able to take that back upstream towards, "Okay, here's where the inventory is. "I have some in this store. "I can't fulfill that clothing item directly from the store, "but I can fulfill it from this one," or, "I have it in another warehouse," when you have that level of awareness and integration, that's high value. >> Yeah, but I want to push back a little bit on you, George, 'cause I do think the invoice ma-, if he can automatically match 94% of the invoices, that is tremendous value. I just think it's so creative when you apply this machine learning to tasks that feel relatively mundane. But if you're speeding your cash flow along, if you get 94% of your invoices done one day faster and you're a multimillion dollar business, what is the direct dollar impact on the bottom line, like, immediately? It's huge. And then you can iterate and move into other processes. I think what's termed a low value transaction is actually a lot higher value than people give it credit. It's just like again, another one we hear about all the time, automation of password reset. Some of these service desks, password reset, I heard a stat, and one of them was 70% of the calls are password reset. So if you could automate password reset, sounds kind of silly and mundane, oh my gosh, it's like 70% of your calls. It's humongous. >> I hear what you're saying. Let me give you another counter example, which was, I think he brought this up. I don't know if it was today or when Michael Dell spoke, which was that Dell's revolution wasn't that they were more efficient than doing what Compaq did. It's that they had a different business model, which was specifically, they got paid before they even procured or assembled the components. >> Or paid for them, right? >> George: Yes, yes. >> They had no inventory carry costs. >> In fact, that meant their working capital, their working capital needs were negative. In fact, the bigger they got, the more money they collected before they had to spend it. That's a different business model. That wasn't automating the invoice matching. That was, we have such good systems that we don't even have to pay for them and then assemble the stuff until after the customer gave us their credit card. >> Right, right, right. >> I think those are the things that new types of applications can make possible. >> Right. Well, we see it time and time again. It's all about scale, it's all about finding inefficiencies, and there's a lot more inefficiencies around than people give credit, as Uber showed with a lot of cars that sit in driveways and Amazon and the public clouds are showing with a lot of inefficient, not used utilization and private data centers. So the themes go on and on, and they're pretty universal. So, exciting keynote. Any last comment before we sign off for today? >> I guess we want to take a close look at Oracle next and see how their roadmap looks like in terms of applying these new technologies, iOT, machine learning, block chain. Because all of these can remake how you build a business. >> All right, that's George Gilbert from Wikibon. I'm Jeff Frick from the CUBE. We are covering ongoing coverage of SAP SAPPHIRE 2017. Thanks for watching, we'll be back with more after this short break. Thanks. (lively music)

Published Date : May 18 2017

SUMMARY :

brought to you by SAP cloud platform Impressions of the kfeynote. all the way to the client server age with R3, You can really tell that he likes the technology, it sort of simplifies the assumptions that you have to make. It's not that we're ignoring it, You put it all in the cloud, you integrate it once. He talked about databases, and databases in the cloud. If they were on prem and you had to support And how does that really change the way and all of a sudden, I can't do that math, and how does that change the way that we go forward? and into the smooth water, that continue to learn as the applications get more data. So that you going to train the system and again, if you can get to a 70% solution, and he said basically, "We're going to grind you into dust, that yes, you want customers which now when you go to a cloud-based application, I forgot the terminology for the different instances. But at the same time, they've got the data. that by far the biggest influencers Nobody talks about the fact I think you sell this stuff differently, It's funny, I heard a funny quote the other day. And forward-looking as well, But one of the things he brought up is Tesla. so that he could stop and tell the Porsche guys And that did change the experience for buying it in that the analysis coming out of the game of one of the machine learning-type apps, But he also now sees around the corner, And I think what he's trying to say is, and he said, "I don't run the company any more. I hesitate to say automate because, as he said, "I can't fulfill that clothing item directly from the store, if he can automatically match 94% of the invoices, It's that they had a different business model, the more money they collected before they had to spend it. that new types of applications can make possible. and Amazon and the public clouds are showing how you build a business. I'm Jeff Frick from the CUBE.

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